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We propose a decorrelation filter (noise-reduction filter) constructed by using the full error covariance matrix information of the spherical harmonic solutions derived from the observations of the Gravity Recovery and Climate Experiment (GRACE) mission. To construct the noisereduction filter, the filter factors are inversely proportional to the eigenvalues of the covariance matrix. Using the designed noise-reduction filter, we can significantly reduce the north-south stripes in monthly GRACE gravity field solutions. Our study shows that the noise-reduction filter can achieve higher signal-to-noise ratio as compared to other filtering methods under consideration, i.e., P3M8 and P4M6 as well as Gaussian smoothing. Using the noise-reduction filter, the estimated mass rates over the entire Antarctica, East Antarctica and West Antarctica (including the Antarctica Peninsula) are -107.38±41.06 Gt/yr, 36.42±14.40 Gt/yr and -147.45±16.78 Gt/yr respectively, consistent with the results from the P3M8 filter and P4M6 combined with Gaussian filter. [ABSTRACT FROM AUTHOR]

The effects of contrast adaptation and contrast area summation (spatial integration) were investigated using a contrast discrimination task. The task consisted of a target of variable size, and a pedestal with a fixed base contrast. Discrimination performance was examined for a condition in which the pedestal size was fixed, equal to the largest target size, and for a condition in which the pedestal size matched the target size and thus varied with it. Repeated performance of the task produced rapid within-session improvements for both conditions. For stimuli with a matching size of target and pedestal, the performance improved only for the larger targets, indicating the development of spatial integration, which was initially absent for these stimuli. However, the improvements were mostly temporary, and were not fully retained between subsequent daily sessions. The temporary nature of the sensitivity gains implies that they resulted, at least in part, from rapid adaptation to the stimulus contrast. We suggest that adaptation decorrelates and thus reduces the spatial noise generated by a high-contrast pedestal, leading to improved spatial integration (area summation) and better contrast sensitivity. A decorrelation model successfully predicted our experimental results. [ABSTRACT FROM AUTHOR]

We carry out a comprehensive error assessment of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) Release‐6 (RL06) solutions from the Center for Space Research (CSR) at the University of Texas at Austin, NASA Jet Propulsion Laboratory (JPL), and Geoforschungszentrum (GFZ). The study covers the period April 2002 to August 2020 and uses two different methods, one based upon open ocean residuals (OOR) and the other a Three‐Cornered Hat (TCH) calculation. General results from the two methods are similar. With 300 km Gaussian smoothing OOR RMS errors for CSR, JPL, and GFZ solutions are ∼2.01, 3.19, and 3.67 cm, respectively. With additional decorrelation filtering OOR RMS values are reduced to ∼1.24, 1.53, and 1.69 cm, respectively. TCH analysis also shows that CSR has the lowest noise levels with similar RMS values, and additional decorrelation filtering reduces error levels. TCH may underestimate errors if there are common errors among geophysical background models. Errors in GFO's first two years (25 solutions for 2018.06 to 2020.08) are comparable to those of GRACE when zonal degree 2 and 3 coefficients are replaced by Satellite Laser Ranging estimates. The OOR method reveals mismodeled intra‐seasonal dynamic ocean signals associated with the Argentine Gyre during de‐aliasing, while the TCH method shows differences between ocean tide models near Australia and Antarctica. Both OOR and TCH RMS analysis offer a means to assess the noise level of GRACE/GFO estimated mass change. The actual uncertainty of GRACE/GFO estimate averaged (or totaled) over a given region is also affected by other error sources. Plain Language Summary: The Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) satellite gravity missions provide global measurements of the Earth gravity change, which can be used to study mass redistribution in the Earth system, such as sea level rise, glacial melting, and land water storage change. However, it is difficult to determine the noise level of GRACE/GFO observations. In this study, we estimate GRACE/GFO noise level using two methods. One is based on GRACE/GFO residuals over the ocean, as the true ocean signals can be predicted. The other method is based on the so‐called Three‐Cornered Hat (TCH) calculation. The OOR estimates show that the noise level of three commonly used GRACE/GFO Release‐6 (RL06) gravity solutions, provided by the Center for Space Research (CSR) at the University of Texas at Austin, US NASA Jet Propulsion Laboratory (JPL), and German Research Centre for Geosciences (GFZ), are about 2.01, 3.19, and 3.67 cm, respectively, when 300 km Gaussian smoothing is applied. The TCH calculation shows similar results. Both OOR and TCH estimates suggests that the CSR solutions shown the lowest noise level. The OOR and TCH calculations also capture some geophysical signals that are related errors in background geophysical models used in GRACE/GFO data processing. Key Points: We provide an error assessment of Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow‐On (GFO) measurements using the open ocean residual (OOR) and Three‐Cornered Hat (TCH) methodsWith 300 km Gaussian smoothing, OOR RMS errors for Center for Space Research (CSR), Jet Propulsion Laboratory (JPL), and Geoforschungszentrum Release‐6 (RL06) are estimated to be ∼2.01, 3.19, and 3.67 cm, respectivelyTCH shows similar results, confirming CSR RL06 has lowest noise level, and both methods capture issues with background geophysical models [ABSTRACT FROM AUTHOR]

A new time series interferometric synthetic aperture radar method is presented based on a strain model. Traditionally, the interferometric phases are optimized based only on a constant set of statistically homogeneous points throughout the observing period, and thus the decorrelated phase cannot be well recovered and possible incoherent (or coherent) phases are (are not) used to optimize the target phase. In the proposed method, a strain model, representing the geophysical relationship of spatially adjacent points' deformations, is employed to optimize the interferometric phases interferogram‐by‐interferogram. The unwrapped phase time series can be estimated from the wrapped interferograms based on the linear iterative weighted least squares method, which is simple and can effectively suppress the decorrelation noise. Both simulations and analysis of data over The Geysers geothermal field (TG), California are conducted, validating that the proposed method can reduce the decorrelations and simultaneously preserve the deformation signals. The displacement results of TG from 2007–2011 L‐band ascending ALOS‐1 data and 2015–2020 C‐band ascending/descending Sentinel‐1 data reveal that (a) the displacement rate of TG is decreasing from 2007–2011 to 2015–2020, and (b) temporally variable displacement signals in addition to steady displacement can be observed from 2015 to 2020 for both the east‐west and the vertical components. Plain Language Summary: The interferometric synthetic aperture radar (InSAR) technique is capable of accurately measuring ground surface displacements at high spatial resolution and large coverage. This paper proposes a strain‐model based InSAR time series method, here referred to as the SIGMA method. The SIGMA method aims to enhance the capability of InSAR to measure displacements and can achieve higher accuracy and density of InSAR displacement measurements. Both simulations and real‐data experiments are conducted to illuminate the benefits of the SIGMA method in the presence of substantial decorrelation noise. Particularly, the SIGMA method is used to investigate the surface displacements of The Geysers geothermal field, California, during 2007–2011 and 2015–2020. These time periods are complementary to those considered in previous studies, providing an important data set to investigate the long‐term evolution of ground surface deformation, as well as the effects of recent fluid injection and production practices in the geothermal field. The new method should be of value for improved geo‐hazards monitoring. Key Points: A new time series interferometric synthetic aperture radar (InSAR) method based on a strain model and iterative weighted least squares is proposedThe method can effectively suppress decorrelation noise and improves the InSAR accuracy and densityThe surface deformation of The Geysers geothermal field, California is investigated with 2007–2011 ALOS‐1 and 2015–2020 Sentinel‐1 data [ABSTRACT FROM AUTHOR]

Mars atmospheric pressure variations induce ground displacements through elastic deformations. The various sensors of the InSight mission were designed in order to be able to understand and correct for these ground deformations induced by atmospheric effects. Particular efforts were made, on one hand, to avoid direct pressure and wind effects on the seismometer and, on the other hand, to have a high performance pressure sensor operating in the same frequency range as the seismometer. As a consequence of these technical achievements and the low background seismic noise of Mars, the InSight mission is opening a new science domain in which the ground displacements can be used to perform atmospheric science. This study presents an analysis of pressure and seismic signals and the relations between them. After a short description of the pressure and seismic sensors, we present an analysis of these signals as a function of local time at the InSight location. Then the coherent signals recorded by both pressure and seismic sensors are described and interpreted in terms of atmospheric signals and ground deformation processes. Two different methods to remove the pressure effects recorded by SEIS sensors are presented, and their efficiency is estimated and compared. These decorrelation methods allow the pressure generated noise to be reduced by a factor of 2 during the active day time period. Finally, an analysis of SEIS signals induced by gravity waves demonstrates the interest of ground displacement measurements to characterize their arrival azimuth. Key Points: Coherence between pressure and seismic measurements is high in the 0.05–0.3 Hz range during active day time periodsAtmospheric noise can be removed efficiently from seismic records in the frequency ranges where coherence is highArrival azimuth of night time atmospheric gravity waves is estimated from SEIS data [ABSTRACT FROM AUTHOR]

Acousto-optic imaging (AOI) enables optical-contrast imaging deep inside scattering samples via localized ultrasound modulation of scattered light. However, the resolution in AOI is inherently limited by the ultrasound focus size, prohibiting microscopic investigations. In recent years advances in the field of digital wavefront-shaping allowed the development of novel approaches for overcoming AOI's acoustic resolution limit. However, these approaches require thousands of wavefront measurements within the sample speckle decorrelation time, limiting their application to static samples. Here, we show that it is possible to surpass the acoustic resolution-limit with a conventional AOI system by exploiting the natural dynamics of speckle decorrelations rather than trying to overcome them. We achieve this by adapting the principles of super-resolution optical fluctuations imaging (SOFI) to AOI. We show that naturally fluctuating optical speckle grains can serve in AOI as the analogues of blinking fluorophores in SOFI, enabling super-resolution by statistical analysis of fluctuating acousto-optic signals. Acousto-optical imaging (AOI) is a technique used for deep tissue microscopy in biomedical applications. The authors use statistical approaches of super-resolution optical fluorescent imaging allowing them to realise high resolution AOI with speckle decorrelation in a much shorter time. [ABSTRACT FROM AUTHOR]

Wavelet transform is a multi-scale signal analysis method. It has the characteristics of low entropy, good timefrequency characteristic, multi-scale characteristic and de-correlation, which makes the wavelet transform widely used in image de-noising and edge detection. The multi-scale detection method mainly uses multiple edge detection operators of different scales to detect the edge of image correctly by effective combination. Wavelet multiscale edge detection method not only has good noise suppression capability, but also has complete edge preservation characteristics, which can take advantage of size and scale to obtain precise single pixel wide edge in edge extraction. The proposed algorithm in this paper uses the wavelet transform to detect the jump edge of the image in row direction and column direction, and then the image edge can be formed under certain rules, and useful edge information can be extracted by means of the multi-scale wavelet transform and the difference between signal and noise under the wavelet transform to multiply wavelet coefficient on the adjacent scale. In suppressing noise at the same time, such algorithm implies the the causal relationship of the edge on different scales, and holds that the edge point is the local modulus maximum point of the scale volume coefficient through the thresholding operation, and remove the noise interference and finally the detailed experiment is carried out to prove that this method can effectively solve the contradiction between extracting edge and restraining noise. [ABSTRACT FROM AUTHOR]

A new sea-level elevation measurement system was introduced, which uses a distributed multi-base forward-scattering mechanism. After introducing the working principle of the system, this study analyses the main influencing factors of relative elevation measurement in detail. It is proved through quantitative expression that the interferometric phase error is the main error source affecting relative elevation measurement. In order to evaluate the system capability and prove that the multi-base InSAR (MbInSAR) can meet the application requirements of gravity field inversion through relative ocean surface elevation measurement, three aspects of decorrelation, geometric decorrelation, volumetric decorrelation, and SNR decorrelation, are analysed as the interferometric phase error sources. [ABSTRACT FROM AUTHOR]

To estimate the motion state of object feature point in image space, an adaptive decorrelation Kalman filtering model is proposed in this paper. The model is based on the Kalman filtering method. A first-order Markov sequence model is used to describe the colored measurement noise. To eliminate the colored noise, the measurement equation is reconstructed and then a cross-correlation between the process noise and the newly measurement noise is established. To eliminate the noise cross-correlation, a reconstructed process equation is proposed. According to the new process and measurement equations, and the noise mathematical characteristics of the standard Kalman filtering method, the parameters involved in the new process equation can be acquired. Then the noise cross-correlation can be successfully eliminated, and a decorrelation Kalman filtering model can be obtained. At the same time, for obtaining a more accurate measurement noise variance, an adaptive recursive algorithm is proposed to update the measurement noise variance based on the correlation method. It overcomes the limitations of traditional correlation methods used for noise variance estimation, thus, a relatively accurate Kalman filtering model can be obtained. The simulation shows that the proposed method improves the estimation accuracy of the motion state of object feature point. [ABSTRACT FROM AUTHOR]

Aurora spectral data, the particular hyperspectral data of auroral spectra, have an irreplaceable research value in bridging the gap between solar activity and terrestrial evolution. Their requirement for high-volume storage and real-time transmission had been a great challenge until we proposed a CPU-paralleled and online-biprediction-based method. As it is no longer applicable because of the recent spectrograph reassembling, this paper presents a replacement strategy combines the unidirectional predictor with the entropy coder of the other dimension, as well as with using smoothing and outlier recognition. The hybrid encoders of Spat-SPCC and Spec-SPCC are developed distinguished by their respective prediction direction. Spat-SPCC tuned on one-day trial data is used for its better capability for compression, in the further comparison with various classical algorithms, it achieves the top-ranking compression performance and has the average processing time of 1 s per file so that its availability for the practical applications is validated. [ABSTRACT FROM AUTHOR]

Abstract In this paper we present a method of zero-padding temporal auto-correlation imaging (ztDCI) for imaging blood flows. Compared with temporal auto-correlation imaging (tDCI), ztDCI effectively slows down the decorrelation speed of speckle frames, so it has wider applicable speed range. We also prove that the combination of tDCI and ztDCI can compensate the non-monotonous trend of ztDCI VS speed and provides higher relative signal to noise rate (rSNR) for slow flows and short exposure times than laser speckle contrast imaging (LSCI). It captures both slow and fast flows independent of camera exposure time which will be an advantage for in vivo or clinical applications. [ABSTRACT FROM AUTHOR]

For normal-hearing (NH) listeners, interaural information in both temporal envelope and temporal fine structure contribute to binaural unmasking of target signals in background noise; however, in many conditions low-frequency interaural information in temporal fine structure produces greater binaural unmasking. For bilateral cochlear-implant (CI) listeners, interaural information in temporal envelope contributes to binaural unmasking; however, the effect of encoding temporal fine structure information in electrical pulse timing (PT) is not fully understood. In this study, diotic and dichotic signal detection thresholds were measured in CI listeners using bilaterally synchronized single-electrode stimulation for conditions in which the temporal envelope was presented without temporal fine structure encoded (constant-rate pulses) or with temporal fine structure encoded (pulses timed to peaks of the temporal fine structure). CI listeners showed greater binaural unmasking at 125 pps with temporal fine structure encoded than without. There was no significant effect of encoding temporal fine structure at 250 pps. A similar pattern of performance was shown by NH listeners presented with acoustic pulse trains designed to simulate CI stimulation. The results suggest a trade-off across low rates between interaural information obtained from temporal envelope and that obtained from temporal fine structure encoded in PT. [ABSTRACT FROM AUTHOR]

The nominally incoherent coda of a scattered wavefield has been shown to be a remarkably sensitive quantitive monitoring tool. Its success is, however, often limited to applications where only moderate or localised changes in the scattering properties of the medium can be assumed. However, the compressional deformation of a relatively homogeneous rock matrix towards failure represents for a monitoring wavefield pronounced changes in both velocity and scattering power often due to a distribution of inelastic changes. A rolling reference wavefield is implemented when applying coda-wave interferometry (CWI) and coda-wave decorrelation (CWD), allowing relative velocity and material scattering power monitoring for such applications. It is demonstrated how this modification enables the qualitative monitoring of stages in material deformation common to unconfined compressive strength tests. In addition, the precursory/subtle onset of material yielding is identifiable in both the CWI and CWD methods, which was not possible when comparing to a fixed reference wavefield. It is, therefore, expected that this approach will enable these coda-based methods to robustly monitor continuous, destructive processes at a variety of scales. Possible applications include critical infrastructure, landslide, and reservoir compaction monitoring where both the subtle continuous and sudden large changes in a material's scattering properties occur. [ABSTRACT FROM AUTHOR]

Spectral decorrelation has been considered an important approach in multispectral image compression to remove the redundancy among bands. In this paper, we propose a novel adaptive spectral decorrelation method based on clustering analysis for Moderate Resolution Imaging Spectroradiometer (MODIS) image compression. The remote sensing image bands are divided into different clusters by the method based on density peak clustering. Then, reversible Karhunen–Loeve transform and polynomial least square estimation are employed to reduce the band redundancy, achieving an effective spectral decorrelation. As shown by the experimental results, our method achieves remarkable bit-saving when compared to the state-of-the-art algorithms on MODIS image data set. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we describe the application of differential radar interferometry for monitoring landslide slopes in the Sochi region under conditions of strong temporal decorrelation of the reflected signals from the underlying surface in images of the TerraSAR-X synthetic aperture radar. Measurements of the movement of the landslide surface became possible due to the use of steadily reflecting objects, e.g., specially designed trihedral corner reflectors with square plates having cut-off external corners. Radiophysical properties of the corners and the criteria for choosing their size and geometry are described in detail. The sensitivity of the position of the phase center of the signal scattered by a corner reflector to undesirable atmospheric phenomena (precipitation occurring inside the corner) is mentioned and substantiated. Based on an analysis of the results of processing four TerraSAR-X images, we show the possibility of measurements with millimeter accuracy in the X-band of the surface displacements of the observed landslide slope with the corner reflectors installed on its surface. [ABSTRACT FROM AUTHOR]

Highlights • Immediate SAR interferometry uses two data sets acquired seconds to minutes apart. • The utility of immediate coherence for water and ice mapping is unaffected by wind. • Immediate coherence is dominated by temporal change and SAR system noise. • An operational, immediate SAR interferometry mission would benefit many end users. Abstract TanDEM-X bistatic and pursuit monostatic InSAR coherence offer different utility for lake ice extent mapping. Both facilitate ice-water discrimination largely independent of the SAR incidence angle but only pursuit monostatic coherence does so under all wind conditions. Relative to backscatter intensity—the basis for most existing mapping approaches—pursuit monostatic coherence offers enhanced utility. Our automated mapping approach combines basic interferometric processing, ice-water classification using a 0.3 coherence threshold and geospatial analysis to separate lakes from land. The approach is developed and demonstrated using TanDEM-X pursuit monostatic data acquired during freeze-up but should also be of use for the mapping of lake ice breakup. Early in the freeze-up season, the extent of lake ice is underestimated due to the commission of new ice—estimated age ≤ 5 days—in the water class. An evaluation of coherence for sample regions reveals three principal—surface cover and cooperative mode dependent—decorrelation sources: temporal change, additive noise and multiplicative noise. TanDEM-X operated in its pursuit monostatic mode for a limited time in support of scientific studies. The introduction of a system with a fully operational capacity to acquire near-simultaneous InSAR images would benefit operational users concerned with lake ice extent mapping and—we expect—many others that deal with water or other rapidly changing features. [ABSTRACT FROM AUTHOR]

Abstract The RMoG (Random-Motion-over-Ground) model is commonly used to obtain tree height values from PolInSAR images. The RMoG model borrows its structure function from conventional RVoG (Random-Volume-over-Ground) model which is limited for modelling structural variety in canopy layer. This paper extends the RMoG model to improve tree height estimation accuracy by using a Fourier-Legendre polynomial as the structure function. The new model is denoted by the RMoG L model. The proposed modification makes height estimation less prone to errors by enabling more flexibility in representing the vertical structure of the vegetation layer. We applied the RMoG L model on airborne P- and L-band PolInSAR images from the Remingstorp test site in southern Sweden. We compared it with the RMoG and the conventional RVoG models using Lidar height map and field data for validation. For P-band, the relative error was equal to 37.5% for the RVoG model, to 23.7% for the RMoG model, and to 18.5% for the RMoG L model. For L-band it was equal to 30.54% for the RVoG model, to 20.02% for the RMoG model, and to 21.63% for the RMoG L. We concluded that the RMoG L model estimates tree height more accurately in P-band, while in L-band the RMoG model was equally good. The RMoG L model is of a great value for future SAR sensors that are more focused than before on tree height and biomass estimation. [ABSTRACT FROM AUTHOR]

The scene restoration effect of the dehazing algorithms usually suffers from double quality interference. First, the dehazing methods based on the atmospheric scattering model (ASM) lead to light loss. Second, the synthetic data used for supervised learning may produce apparent data deviation from the real hazy scene, which seriously weakens the generalization ability of the model. To address the above problems, we propose an uncorrelated graph dehazing model for real-world scenes. The process firstly eliminates the correlation in the representation space by establishing a directed acyclic graph with isolated points, thus enhancing the generalization performance of the model. Secondly, to suppress over-exposure that may occur on real-world data, the proposed model training is performed with a combination of light control. This work improves the ASM and constructs a new dataset applicable to natural haze scenes. Finally, the effectiveness of the proposed method can be verified through multiple experimental comparisons. [ABSTRACT FROM AUTHOR]

Aims. MASCARA and bRing are photometric surveys designed to detect variability caused by exoplanets in stars with mV < 8.4. Such variability signals are typically small and require an accurate calibration algorithm, tailored to the survey, in order to be detected. This paper presents the methods developed to calibrate the raw photometry of the MASCARA and bRing stations and characterizes the performance of the methods and instruments. Methods. For the primary calibration, a modified version of the coarse decorrelation algorithm is used, which corrects for the extinction due to the earth's atmosphere, the camera transmission, and intrapixel variations. Residual trends are removed from the light curves of individual stars using empirical secondary calibration methods. In order to optimize these methods, as well as characterize the performance of the instruments, transit signals were injected in the data. Results. After optimal calibration an RMS scatter of 10 mmag at mV ~ 7.5 is achieved in the light curves. By injecting transit signals with periods between one and five days in the MASCARA data obtained by the La Palma station over the course of one year, we demonstrate that MASCARA La Palma is able to recover 84.0, 60.5 and 20.7% of signals with depths of 2, 1 and 0.5%, respectively, with a strong dependency on the observed declination, recovering 65.4% of all transit signals at δ > 0° versus 35.8% at δ < 0°. Using the full three years of data obtained by MASCARA La Palma to date, similar recovery rates are extended to periods up to ten days. We derive a preliminary occurrence rate for hot Jupiters around A-stars of >0.4%, knowing that many hot Jupiters are still overlooked. In the era of TESS, MASCARA and bRing will provide an interesting synergy for finding long-period (>13.5 days) transiting gas-giant planets around the brightest stars. [ABSTRACT FROM AUTHOR]

Long-term surface deformation monitoring of highways is crucial to prevent potential hazards and ensure sustainable transportation system safety. DInSAR technique shows its great advantages for ground movements monitoring compared with traditional geodetic survey methods. However, the unavoidable influences of the temporal and spatial decorrelation have brought restrictions for traditional DInSAR on the application for ribbon infrastructures deformation monitoring. In addition, PS and SBAS techniques are not suitable for the area where adequate natural high coherent points cannot be detected. Due to this, we designed an integrated highway deformation monitoring algorithm based on CRInSAR technique in this paper, the processing flow including Corner Reflectors (CR) identification, CR baseline network establishment, phase unwrapping, and time series highway deformation estimation. Both the simulated and real data experiments are conducted to assess and validate the algorithm. In the scenario using simulated data, 10 different noise levels are added to test the performance under different circumstances. The RMSE of linear deformation velocities for 10 different noise levels are obtained and analyzed, to investigate how the accuracy varies with noise. In the real data experiment, part of a highway in Henan, China is chosen as the test area. Six PALSAR images acquired from 22 December 2008 to 09 February 2010 were collected and 12 CR points were installed along the highway. The ultimate time series deformation estimated show that all the CR points are stable. CR04 is undergoing the most serious subsidence, with the maximum magnitude of 13.71 mm over 14 months. Field leveling measurements are used to assess the external deformation accuracy, the final RMSE is estimated to be ± 2. 2 mm, which indicates good accordance with the result of leveling. [ABSTRACT FROM AUTHOR]

An accurate and flexible real-time digital image correlation (RT-DIC) system utilizing a pipelined CPU and GPU parallel computing framework is proposed. First, the respective advantages of CPU and GPU in performing the fast Fourier transform-based cross-correlation (FFT-CC) algorithm and the inverse-compositional Gauss Newton (IC-GN) algorithm of the employed path-independent DIC (PI-DIC) method are elucidated. Second, based on the different properties and performances of CPU and GPU, a pipelined system framework unifying five Variants of combinations of CPU and GPU is proposed, which can be flexibly applied to various practical applications with different requirements of measurement scales and speeds. Last, both the accuracy and speed of the entire pipelined framework are verified by a PC implementation of the RT-DIC system integrating Variants 2–5. Variants 2 and 5 are also implemented on an iPhone 5S for the feasibility investigation of realizing a portable RT-DIC system on mobile devices using the same framework. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate the vascular anatomy of eyes with Best vitelliform macular dystrophy (BVMD) using optical coherence tomography angiography (OCTA). Methods: This retrospective case-control study enrolled 11 consecutive BVMD patients and 13 age-matched healthy participants. Both eyes of each participant were imaged using a macular OCTA scan (3 × 3 mm) by 70-kHz 840-nm spectral-domain OCT. The flow signal was calculated using the split-spectrum amplitude-decorrelation angiography (SSADA) algorithm. Results: Qualitative analysis showed uneven hypo- and hyperintense signal changes at the choriocapillary level in OCTA images of BVMD patients. Quantitative analysis showed significant reductions in the flow density of the superficial vascular layer (whole: 49.2% vs. 53.9%, p < 0.001) and the choriocapillary flow area (5.1 vs. 5.5 mm2, p = 0.02) in BVMD patients compared to controls. The choriocapillary flow area in the postvitelliform group was reduced compared to that of the vitelliform group. There was a statistically significant association between choriocapillary flow area and superficial vascular flow density (p = 0.045), choriocapillary flow area and foveal avascular zone area (p = 0.03). Conclusions: Vascular changes in BVMD were apparent in the choriocapillary layer. The changes became more striking in late stages of the disease. OCTA provides useful quantitative measurements for staging and monitoring the progression of BVMD. [ABSTRACT FROM AUTHOR]

This communication presents a new technique to reduce the correlation coefficient value between adjacent antenna elements in multiple-input-multiple-output (MIMO) configurations. Unlike the conventional works which utilize port isolation enhancement methods for this purpose, the proposed approach adopts decorrelation of the radiation patterns of individual elements. To achieve this, a phase-gradient frequency selective surface is used as a superstrate above the antenna elements in a low profile Fabry–Perot cavity configuration. The effectiveness of the method is demonstrated by designing the system for a two-element MIMO antenna at 5.25 GHz. The proposed technique results in more than 95% reduction in the correlation coefficient value, thus projecting a better MIMO performance. [ABSTRACT FROM AUTHOR]

Unwrapping and de-noising are key processes for the restoration of phase data in the presence of high speckle decorrelation noise. Usually, there are two strategies to deal with noisy wrapped phase: de-noising before unwrapping, or unwrapping before de-noising. This paper aims at comparing the robustness and efficiency of the strategies. Six combinations which belong to different strategies are compared in this paper. Ten simulated phase maps with progressive noise standard deviations are generated based on the realistic speckle decorrelation noise to evaluate the performances of the approaches. The results of simulation show that de-noising with windowed Fourier transform filtering before unwrapping with the algorithm based on least-squares and iterations which belongs the first strategy has the best accuracy and acceptable computation speed for the restoration of high noisy phase data. Application of selected methods to experimental phase data from digital holography validated the analysis. [ABSTRACT FROM AUTHOR]

Direction of arrival (DOA) estimation algorithms based on sparse Bayesian inference (SBI) can effectively estimate coherent sources without recurring to extra decorrelation techniques, and their estimation performance is highly dependent on the selection of sparse prior. Specifically, the specified sparse prior is expected to concentrate its mass on the zero and distribute with heavy tails; otherwise, these algorithms may suffer from performance degradation. In this paper, we introduce a new sparse-encouraging prior, referred to as “Gauss-Exp-Chi2” prior, and develop an efficient DOA estimation algorithm for a mixture of uncorrelated and coherent sources under a hierarchical SBI framework. The Gauss-Exp-Chi2 prior distribution exhibits a sharp peak at the origin and heavy tails, and this property makes it an appropriate prior to encourage sparse solutions. A three-layer hierarchical sparse Bayesian model is established. Then, by exploiting variational Bayesian approximation, the model parameters are estimated by alternately updating until Kullback-Leibler (KL) divergence between the true posterior and the variational approximation becomes zero. By constructing the source power spectra with the estimated model parameters, the number and locations of the highest peaks are extracted to obtain source number and DOA estimates. In addition, some implementation details for algorithm optimization are discussed and the Cramér-Rao bound (CRB) of DOA estimation is derived. Simulation results demonstrate the effectiveness and favorable performance of the proposed algorithm as compared with the state-of-the-art sparse Bayesian algorithms. [ABSTRACT FROM AUTHOR]

A method utilizing matrix analysis has been presented for a full-area three-flat test. With the aid of the Moore–Penrose pseudoinverse of a circulant matrix, a set of closed mathematical formulas has been derived to obtain the absolute profiles of samples. According to the simulation results, the matrix analysis method shows better performances for determining the absolute profiles and suppressing the decorrelation residuals of the reconstructed wavefronts, compared to the iterative method. Three optical flats with 135-mm apertures are measured. The results obtained with the new method agree well with those obtained with the iterative algorithm and the classical three-flat test. Furthermore, the relationship between the decorrelation residual and the wavefront error introduced in the rotation measurement has been studied. Theoretical and experimental results show that the odd-symmetric component contributes significantly to the decorrelation residual. [ABSTRACT FROM AUTHOR]

Random and high-agreement secret key generation from noisy wideband channels is challenging due to the autocorrelation inside the channel samples and compromised cross correlation between channel measurements of two keying parties. This paper studies the signal preprocessing algorithms to establish high-agreement uncorrelated secret key in the presence of channel independent eavesdroppers. We first propose a general mathematical model for various preprocessing schemes, including principal component analysis (PCA), discrete cosine transform (DCT) and wavelet transform (WT). Among preprocessing schemes, PCA is proved to achieve the optimal secret key rate. Next, PCA with common eigenvector has been found to outperform PCA with private eigenvector in terms of an overall consideration of key agreement, information leakage, and computational expense. Then, we propose a system level design of key generation, including quantization, information reconciliation, and privacy amplification. Numerical results verify that the key generation enhanced by PCA with common eigenvector can achieve secret key with high key generation rate, low key error rate, and good randomness. [ABSTRACT FROM AUTHOR]

In horizontal stereophony, it is known that interchannel correlation relates to the horizontal spread of a phantom auditory image. However, little is known about the perceptual effect of interchannel correlation on vertical image spread (VIS) between two vertically-arranged loudspeakers. The present study investigates this through two subjective experiments: (i) a multiple comparison of relative VIS for stimuli with varying degrees of correlation; and (ii) the absolute measurement of upper and lower VIS boundaries for extreme stimuli conditions. Octave-band (center frequencies: 63 Hz to 16 kHz) and broadband pink noise signals have been decorrelated using two techniques: all-pass filtering and complementary comb-filtering. These stimuli were presented from vertically-spaced loudspeaker pairs at three azimuth angles (0°, ±30°, and ±110°), with each angle assessed discretely. Both the relative and absolute test results show no significant effect of vertical correlation on VIS for the 63 Hz, 125 Hz, and 250 Hz bands. For the 500 Hz band and above, there is a general tendency for VIS to increase as correlation decreases, which is observed for both decorrelation methods. This association is strongest at 0° azimuth for the 500 Hz and 1 kHz bands; at ±30° for 8 kHz and Broadband; and at ±110° for 2 kHz, 4 kHz, and 16 kHz. The 8 kHz band at ±30° has the strongest association of all conditions--post-hoc objective analysis indicates a potential relationship between HRTF localization cues (pinna filtering) and VIS perception within this frequency region. Furthermore, the absolute test results suggest that changes of VIS from interchannel decorrelation are fairly slight, with only the Broadband and 16 kHz bands showing a significant increase. The deviations of boundary scores also suggest a difficulty grading absolute VIS and/or potential disagreements among listeners. [ABSTRACT FROM AUTHOR]

Background: Deviation in gait performance from normative data of healthy cohorts is used to quantify gait ability. However, normative data is influenced by anthropometry and such differences among subjects impede accurate assessment. De-correlation of anthropometry from gait parameters and mobility measures is therefore desirable. Methods: 87 (42 male) healthy subjects varying form 21 to 84 years of age were assessed on gait parameters (cadence, ankle velocity, stride time, stride length) and mobility measures (the 3-meter/7-meter Timed Up-and-Go, 10-meter Walk Test). Multiple linear regression models were derived for each gait parameter and mobility measure, with anthropometric measurements (age, height, body mass, gender) and self-selected walking speed as independent variables. The resulting models were used to normalize the gait parameters and mobility measures. The normalization’s capability in de-correlating data and reducing data dispersion were evaluated. Results: Gait parameters were predominantly influenced by height and walking speed, while mobility measures were affected by age and walking speed. Normalization de-correlated data from anthropometric measurements from |rs| < 0.74 to |rs| < 0.23, and reduced data dispersion by up to 69%. Conclusion: Normalization of gait parameters and mobility measures through linear regression models augment the capability to compare subjects with varying anthropometric measurements. [ABSTRACT FROM AUTHOR]

Slow-moving landslides are numerous in mountainous areas and pose a large threat to populations. Many observations show that their kinematics is driven by climatic forcings and earthquakes. In this study, we document the complex interaction between those two forcings on the slow-moving landslide kinematics, based on the retrieval of landslide displacements over 28-years using optical satellite images. To overcome the decorrelation effect over this large time-span, and possible misalignment between images, we develop a method that uses the redundancy of displacement fields from image pairs to derive a robust time-series of displacement. The method is tested on the 28-year long SPOT1/5-Pléiades archive, over an area in Peru affected by both earthquakes and rainfall. Errors are estimated on stable areas and by comparison with one 13-year long and eleven 3-year long GPS time-series on the Maca landslide. The methodology diminishes by up to 30% the uncertainty and reduces significantly the gaps due to decorrelation. The data set allows detecting 3 major landslides, moving at a rate of 35 to 50 m over 28 years, and smaller landslides with lower displacement rates. Time-series obtained over the three main landslides provide interesting results of their long-term kinematics, primarily driven by precipitation. We propose simple statistical hydro-kinematic models, relating yearly motion to seasonal rainfall, to explain the observed time-series. We found that annual precipitation is controlling the landslide displacements after a certain rainfall threshold is reached. Besides this control, we show the possible impact of a local Mw 5.4 earthquake in 1991 on the kinematics of the Maca landslide. Our results suggest that the earthquake accelerated the landslide and has an effect during several years on the precipitation threshold required for triggering a motion. These results suggest that the rainfall threshold can vary in time following strong earthquakes shaking. [ABSTRACT FROM AUTHOR]

This paper presents a detailed analysis of the applicability and benefits of baseline-dependent averaging (BDA) in modern radio interferometers and in particular the Square Kilometre Array. We demonstrate that BDA does not affect the information content of the data other than a well-defined decorrelation loss for which closed form expressions are readily available. We verify these theoretical findings using simulations. We therefore conclude that BDA can be used reliably in modern radio interferometry allowing a reduction of visibility data volume (and hence processing costs for handling visibility data) by more than 80 per cent. [ABSTRACT FROM AUTHOR]

Abstract: It is generally held that subtle changes in sandy environments are very difficult to detect in imagery. Nonetheless, this study demonstrates how synthetic aperture radar (SAR) interferometric decorrelation can be used to identify changes in individual sand dunes. The use of coherence maps over time facilitates the analysis of dune dynamics, both temporally and spatially. The Ashdod‐Nizzanim coastal dunes, along the southern coastal plain of Israel, were chosen as an illustrative example of the analysis of dune dynamics. High‐resolution TerraSAR‐X (TSX) radar images covering the entire research area were acquired for the period February to July 2012, together with meteorology data (wind and rain) for the area. The coherence results enabled the stability of individual dunes to be described as a function of time. It was found that the dune crests were more stable than the windward slopes and that the degree of stability was dependent on the distance of the dune from the sea. The results of this study show the potential of using interferometric synthetic aperture radar (InSAR) decorrelation for aeolian studies, even in areas characterized by low coherence. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Intensity saturation can cause decorrelation phenomenon and decrease the measurement accuracy in digital image correlation (DIC). In the paper, the grey intensity adjustment strategy is proposed to improve the measurement accuracy of DIC considering the effect of intensity saturation. First, the grey intensity adjustment strategy is described in detail, which can recover the truncated grey intensities of the saturated pixels and reduce the decorrelation phenomenon. The simulated speckle patterns are then employed to demonstrate the efficacy of the proposed strategy, which indicates that the displacement accuracy can be improved by about 40% by the proposed strategy. Finally, the true experimental image is used to show the feasibility of the proposed strategy, which indicates that the displacement accuracy can be increased by about 10% by the proposed strategy. [ABSTRACT FROM AUTHOR]

Different transforms used in binding a secret key to correlated physical-identifier outputs are compared. Decorrelation efficiency is the metric used to determine transforms that give highly-uncorrelated outputs. Scalar quantizers are applied to transform outputs to extract uniformly distributed bit sequences to which secret keys are bound. A set of transforms that perform well in terms of the decorrelation efficiency is applied to ring oscillator (RO) outputs to improve the uniqueness and reliability of extracted bit sequences, to reduce the hardware area and information leakage about the key and RO outputs, and to maximize the secret-key length. Low-complexity error-correction codes are proposed to illustrate two complete key-binding systems with perfect secrecy, and better secret-key and privacy-leakage rates than existing methods. A reference hardware implementation is also provided to demonstrate that the transform-coding approach occupies a small hardware area. [ABSTRACT FROM AUTHOR]

A new sequential blind source separation algorithm is proposed based on intelligent single particle optimization. The signal variability is used as the objective function and the separation vector is transformed by using the spherical coordinate transform method. The intelligent single particle optimization is used for solving the objective function. By de-correlation method, the separated source signal component is removed from the mixed signals, and source signal could be separated out respectively according to the decreasing order of the signal variability. Simulation results show that the proposed separation algorithm can realize sequential separation of source signal efficiently and the separation precision is very high. [ABSTRACT FROM AUTHOR]

Multiple‐input multiple‐output (MIMO) systems offer significant enhancements in terms of their data rate and channel capacity compared to traditional systems. However, correlation degrades the system performance and imposes practical limits on the number of antennas that can be incorporated into portable wireless devices. The use of switched parasitic antennas (SPAs) is a possible solution, especially where it is difficult to obtain sufficient signal decorrelation by conventional means. The covariance matrix represents the correlation present in the propagation channel, and has significant impact on the MIMO channel capacity. The results of this work demonstrate a significant improvement in the MIMO channel capacity by using SPA with the knowledge of the covariance matrix for all pattern configurations. By employing the “water‐pouring algorithm” to modify the covariance matrix, the channel capacity is significantly improved compared to traditional systems, which spread transmit power uniformly across all the antennas. A condition number is also proposed as a selection metric to select the optimal pattern configuration for MIMO‐SPAs. [ABSTRACT FROM AUTHOR]

This work proposes singular value decomposition (SVD) to separate the signal from a noisy X-ray image sequence without any prior knowledge of the noise. SVD is based on the theory that the noise is always uncorrelated to the signal in a noisy image, and SVD, which belongs to Blind Source Separation (BSS), can decorrelate the signal from the noise components. To apply this proposed denoising method, two groups of X-ray images produced at 25 kV & 20 mAs and 34 kV & 20 mAs are sampled. To measure the proposed denoising method, ROIs with differing glandularity are selected. This work supports the use of SVD in X-ray image denoising. Normally, the separated signal will be less noisy when more noisy images are included for separating signals. Compared with other classical denoising methods, SVD is superior in reducing noise and improving CNR or SNR. [ABSTRACT FROM AUTHOR]

In multiple scattering media, the coda wave decorrelation relates linearly to the scattering cross-section of structural change when the change is small compared to the wavelength. In practical applications, we assume that the total decorrelation induced by changes in the medium is the sum of the decorrelation induced by each elementary change. In this article, we investigate the validity of this linear approximation for extended changes larger than the wavelength, and the possible signature of the change orientation. Coda waves are simulated using a 2-D finite-difference model in multiple scattering media. We perform a parametric analysis of the decorrelation induced by extended structural changes of various length and orientation, as well as the mutual influence between two identical changes separated by a varying distance. Our findings are: (1) we underestimate the length of the change when it exceeds one wavelength. (2) the decorrelation value is sensitive to the orientation of extended changes at distances smaller than four mean free paths between the source and the receiver. (3) two simultaneous changes are interacting within a distance of the order of the mean free path, but can be considered independent at a separation distance larger than a few mean free paths. [ABSTRACT FROM PUBLISHER]

Digital volume correlation (DVC) has been widely accepted as an effective experimental technique for quantifying full-field internal 3D deformation of solid materials and structures under external loading. However, conventional DVC using a fixed reference volume image generally fails when serious decorrelation occurs in deformed volume images due to large deformation or other reasons. In this work, an accurate and simple incremental DVC method with nearest subvolume offset is proposed for large deformation measurement. Specifically, the reference subvolumes in the updated reference volume images are translated to nearest integer-voxel positions, rather than being interpolated at subvoxel locations. The translated reference subvolumes, within which all correlation points locate at integer-voxel positions, are then tracked in the rest deformed volume images to retrieve incremental displacement fields. The obtained incremental displacement fields are then accumulated to previously obtained displacement fields to determine the overall displacements. By using the simple nearest subvolume offset approach, subvoxel intensity interpolation for the updated reference subvolumes is entirely avoided, thus not only eliminating the bias error associated with imperfect subvoxel intensity interpolation, but also increasing the computational efficiency of incremental DVC calculation by approximately 2.5 times. The accuracy, efficiency and practicality of the presented incremental DVC are demonstrated by analyzing two sets of volume images with large deformation generated in numerically simulated and real-world experiments. [ABSTRACT FROM AUTHOR]

To fast estimate high-dimensional ambiguities, we propose a new lattice reduction algorithm based on QR decomposition, which achieves fast integer transformation through an iterative strategy of whole size reduction and the deep insertion of minimum basis vectors. It acquires better basis vectors for ambiguity resolution. The feasibility of the proposed algorithm is verified by comparing its performance with those of LAMBDA, LLL, the parallel Cholesky-based reduction algorithm with ascending sorting (ASCE), and a modified LLL algorithm with deep insertions (PotLLL) under three experimental scenarios. The Hermite defect and defined length ratio are used to measure the reduction quality. Both metrics verify that our proposed method acquires a good reduced basis for accelerating the ambiguity search. To evaluate the practical ambiguity resolution behaviour, we tracked the runtime of ambiguity resolution. The results show that the computational efficiency of the proposed algorithm is better than those of the comparative algorithms. [ABSTRACT FROM AUTHOR]

The ability to control high-intensity focused ultrasound (HIFU) thermal ablation using echo decorrelation imaging feedback was evaluated in ex vivo bovine liver. Sonications were automatically ceased when the minimum cumulative echo decorrelation within the region of interest exceeded an ablation control threshold, determined from preliminary experiments as -2.7 (log-scaled decorrelation per millisecond), corresponding to 90% specificity for local ablation prediction. Controlled HIFU thermal ablation experiments were compared with uncontrolled experiments employing two, five or nine sonication cycles. Means and standard errors of the lesion width, area and depth, as well as receiver operating characteristic curves testing ablation prediction performance, were computed for each group. Controlled trials exhibited significantly smaller average lesion area, width and treatment time than five-cycle or nine-cycle uncontrolled trials and also had significantly greater prediction capability than two-cycle uncontrolled trials. These results suggest echo decorrelation imaging is an effective approach to real-time HIFU ablation control. [ABSTRACT FROM AUTHOR]

This paper explores the wind noise reduction mechanism of porous microphone windscreens by investigating the spatial correlation of wind noise. First, the spatial structure of the wind noise signal is studied by simulating the magnitude squared coherence of the pressure measured with two microphones at various separation distances, and it is found that the coherence of the two signals decreases with the separation distance and the wind noise is spatially correlated only within a certain distance less than the turbulence wavelength. Then, the wind noise reduction of the porous microphone windscreen is investigated, and the porous windscreen is found to be the most effective in attenuating wind noise in a certain frequency range, where the windscreen diameter is approximately 2 to 4 times the turbulence wavelengths (2 < D0/ξ < 4), regardless of the wind speed and windscreen diameter. The spatial coherence between the wind noise outside and inside a porous microphone windscreen is compared with that without the windscreen, and the coherence is found to decrease significantly when the windscreen diameter is approximately 2 to 4 times the turbulence wavelengths, corresponding to the most effective wind noise reduction frequency range of the windscreen. Experimental results with a fan are presented to support the simulations. It is concluded that the wind noise reduction mechanism of porous microphone windscreens is related to the spatial decorrelation effect on the wind noise signals provided by the porous material and structure. [ABSTRACT FROM AUTHOR]

A hybrid ensemble-3DVar (En3DVar) system is developed and compared with 3DVar, EnKF, "deterministic Forecast" EnKF (DfEnKF), and pure En3DVar for assimilating radar data through perfect-model observing system simulation experiments (OSSEs). DfEnKF uses a deterministic forecast as the background and is therefore parallel to pure En3DVar. Different results are found between DfEnKF and pure En3DVar: 1) the serial versus global nature and 2) the variational minimization versus direct filter updating nature of the two algorithms are identified as the main causes for the differences. For 3DVar (EnKF/DfEnKF and En3DVar), optimal decorrelation scales (localization radii) for static (ensemble) background error covariances are obtained and used in hybrid En3DVar. The sensitivity of hybrid En3DVar to covariance weights and ensemble size is examined. On average, when ensemble size is 20 or larger, a 5%-10% static covariance gives the best results, while for smaller ensembles, more static covariance is beneficial. Using an ensemble size of 40, EnKF and DfEnKF perform similarly, and both are better than pure and hybrid En3DVar overall. Using 5% static error covariance, hybrid En3DVar outperforms pure En3DVar for most state variables but underperforms for hydrometeor variables, and the improvement (degradation) is most notable for water vapor mixing ratio qy (snow mixing ratio qs). Overall, EnKF/DfEnKF performs the best, 3DVar performs the worst, and static covariance only helps slightly via hybrid En3DVar. [ABSTRACT FROM AUTHOR]

In this paper, a novel decorrelation-based concurrent digital predistortion (DPD) solution is proposed for dual-band transmitters (TXs) employing a single wideband power amplifier (PA), and utilizing only a single feedback receiver path. The proposed decorrelation-based parameter learning solution is both flexible and simple, and operates in a closed-loop manner, opposed to the widely applied indirect learning architecture. The proposed decorrelation-based learning and DPD processing can also be effectively applied to more ordinary single carrier/band transmissions, as well as generalized to more than two transmit bands. Through a comprehensive analysis covering both the DPD parameter learning and the main path processing, it is shown that the complexity of the proposed concurrent DPD is substantially lower compared with the other state-of-the-art concurrent DPD methods. Extensive set of simulation and RF measurement results are also presented, using base-station PAs as well as a commercial LTE-Advanced mobile PA, to evaluate and validate the effectiveness of the proposed DPD solution in various real world scenarios, incorporating both single-band and dual-band TX cases. The simulation and RF measurement results demonstrate excellent linearization performance of the proposed concurrent DPD, even outperforming current state-of-the-art methods, despite the significantly lower complexity. [ABSTRACT FROM AUTHOR]

Representing the spherical harmonic spectrum of a field on the sphere in terms of its amplitude and phase is termed as its polar form. In this study, we look at how the amplitude and phase are affected by linear low-pass filtering. The impact of filtering on amplitude is well understood, but that on phase has not been studied previously. Here, we demonstrate that a certain class of filters only affect the amplitude of the spherical harmonic spectrum and not the phase, but the others affect both the amplitude and phase. Further, we also demonstrate that the filtered phase helps in ascertaining the efficacy of decorrelation filters used in the grace community. [ABSTRACT FROM AUTHOR]

The purpose of the present work is to establish decorrelation estimates at distinct energies for some random Schrödinger operator in dimension one. In particular, we establish the result for some random operators on the continuum with alloy-type potential. These results are used to give a description of the spectral statistics. [ABSTRACT FROM AUTHOR]

We study the diffusion of magnetic field lines in turbulence with magnetic shear. In the first part of the series, we developed a quasi-linear theory for this type of scenario. In this article, we employ the so-called DeCorrelation Trajectory method in order to compute the diffusion coefficients of stochastic magnetic field lines. The magnetic field configuration used here contains fluctuating terms which are described by the dimensionless functions bi(X, Y, Z), i=(x, y) and they are assumed to be Gaussian processes and are perpendicular with respect to the main magnetic field B0. Furthermore, there is also a z-component of the magnetic field depending on radial coordinate x (representing the gradient of the magnetic field) and a poloidal average component. We calculate the diffusion coefficients for magnetic field lines for different values of the magnetic Kubo number K, the dimensionless inhomogeneous magnetic parallel and perpendicular Kubo numbers K‖ B; K⊥ B , as well as Kav = bav y K‖ B/K⊥ B . [ABSTRACT FROM AUTHOR]

Diffuse Field Modeling uses decorrelation filters based on the statistical description of reverberation to approximate the expected measurements on an array of outward-facing cardioid microphones in an acoustic diffuse field. The cardioid microphones are formed from linear combinations of an altered B-Format Room Impulse Response and, in conjunction with channel-specific decorrelation filters, are used to drive inward-facing loudspeakers. This third publication is an extension of two previous publications: Part I [1] presented the physical justification and filter design, and Part II [2] presented a perceptual evaluation of the algorithm for both a large and small loudspeaker array. The current paper presents a method to generate decorrelation filters for three-dimensional loudspeaker arrays with arbitrary angular spacing as well as for binaural configurations. The spatial structure of the ensemble of filters is determined using numerical simulation and the length and frequency-spacing of the constituent bandpass filters is based on estimates of the RT60 of the B-Format Room Impulse Response. [ABSTRACT FROM AUTHOR]