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Having a robust and accurate grid synchronization unit for distributed generators (DGs) has been accentuated due to rapidly growing integration of inverter‐based DGs to the autonomous microgrids. Although most of the synchronization methods are based on the phased locked loops (PLL) technique, digital filters could result in more salient dynamic performance in non‐ideal sinusoidal situations. This paper presents a novel digital filter as a grid synchronization method that overcomes the flaws of conventional PLLs under harmonic distorted and unbalanced cases as well as large delay of window‐based digital filters. For the sake of computational advantages, the proposed method is executed in two distinct offline and online stages. In the offline stage, the second‐order Taylor series expansion approximation of the bandpass oscillatory signal calculates the state‐transition matrices and state vectors. Then, by applying the concept of Kalman filter, the state vectors are updated in the online calculation section much easier and faster compared to all‐online approach. Compared to the existing methods, the proposed method generates a dynamic response with less settling time, more accuracy, and immunity against harmonic distortion, imbalances, and noise. [ABSTRACT FROM AUTHOR]

Effective data analysis ideally requires the analyst to have high expertise as well as high knowledge of the data. Even with such familiarity, manually pursuing all potential hypotheses and exploring all possible views is impractical. We present DataSite, a proactive visual analytics system where the burden of selecting and executing appropriate computations is shared by an automatic server-side computation engine. Salient features identified by these automatic background processes are surfaced as notifications in a feed timeline. DataSite effectively turns data analysis into a conversation between analyst and computer, thereby reducing the cognitive load and domain knowledge requirements. We validate the system with a user study comparing it to a recent visualization recommendation system, yielding significant improvement, particularly for complex analyses that existing analytics systems do not support well. [ABSTRACT FROM AUTHOR]

This paper develops a tool kit for designing low-pass filters to exhibit the smallest possible phase drop. Based solely on the stopband requirements, it is thus possible to find the best order for a filter to be employed in a feedback loop. That is shown for two much-used filter families, Butterworth and Bessel, in cases where the filter is specified to have a minimum attenuation above a certain frequency. It is argued that the phase drop can be represented by an equivalent filter delay. Design tools are then developed, which do not depend on the precise dynamics of the application process. The tools comprise not only the means for determining the optimal filter order and bandwidth, but also formulae and tables useful for obtaining the resulting filter delay. A simple approximation is subsequently developed, which links the minimum obtainable delay directly to said requirements. The filter order need not be known to apply this expression, and the filter family is represented in it by no more than a single constant. This rule of thumb is finally adapted to the area of anti-aliasing filters and there briefly compared to approximative formulae found in existing literature. [ABSTRACT FROM AUTHOR]

This paper deals with the smart applications of multirate digital signal processing. The two major operations are accomplished in consumer electronics and communication engineering. The process of reducing the sampling frequency of a sampled signal is called decimation. In the usage of decimating filters, only a portion of the out-of-pass band frequencies aliases into the pass band, in systems wherein different parts operate at different sample rates. A filter design, tuned to the aliasing frequencies all of which can otherwise stealth into the pass band, not only provides multiple stop bands but also exhibits computational efficiency and performance superiority over the single stop band design. The proposed method of transmultiplexer using decimation and interpolation filters analysis procedure is not only efficient but also opens up a new vista of being simple and elegant to compute for the desired over and above transmultiplexer. [ABSTRACT FROM AUTHOR]

Mitigation of electromagnetic inference (EMI) is currently a challenge for scien-tists and designers in order to cope with electromagnetic compatibility (EMC) compliance in switching mode power supply (SMPS) and ensure the reliability of the whole system. Standard filtering techniques: passive and active ones present some insufficiency in terms of performance at high frequencies (HF) because analog components would no longer be controllable and this is mainly due to their parasitic elements. So developing EMI digital filters is very interesting, especially with the embedment of a machine control system on a field programmable gate array (FPGA) chip. In this paper, we present a design of an active digital EMI filter (ADF) to be integrated in a drive train system of an electric vehicle (EV). Hardware design as well as FPGA implementation issues have been presented to prove the efficiency of the developed digital filtering structure. [ABSTRACT FROM AUTHOR]

Abstract Median filter (MF) is a content preserving nonlinear filter, employed to hide traces of image manipulations, affecting the reliability of manipulation detection techniques. Thus, median filter detection is a major concern for digital image forensics (DIF) experts. The methods used for median filter detection (MFD) are computationally expensive as high dimensionality of feature vectors are employed. This paper proposes an effective method for blind median filter detection based on streaking effect of the median filter. The method offered in the paper is built on experimental observation that the percentage streak area (psa) of an image increases on repetitive median filtering of the image, the rate at which psa increases for median filtered images is different from the rate at which psa increases for unfiltered images. A feature vector based on the observation is extracted from three different image datasets UCID, BOSS and Dresden and feed to Support Vector Machine (SVM) to perform 10-fold cross validation using linear kernel. The results obtained, using a three-dimensional feature vector, demonstrates efficacy of the proposed method. [ABSTRACT FROM AUTHOR]

Power line harmonic noise generated by power lines during the seismic data acquisition in land and marine seismic surveys generally appears as a single frequency with 50/60 Hz (or multiples of these frequencies) and contaminates seismic data leading to complicate the identification of fine details in the data. Commonly applied method during seismic data processing to remove the harmonic noise is classical notch filter (or very narrow band-stop filter), however, it also attenuates all recorded data around the notch frequencies and results in a complete loss of available information which corresponds to fine details in the seismic data. In this study, we introduce an application of the algorithm of iterative trimmed and truncated mean filter method (ITTM) to remove the harmonic noise from seismic data, and here, we name the method as local ITTM (LITTM) since we applied it to the seismic data locally in spectral domain. In this method, an optimal value is iteratively searched depending on a threshold value by trimming and truncating process for the spectral amplitude samples within the specified spectral window. Therefore, the LITTM filter converges to the median, but, there is no need to sort the data as in the case of conventional median filters. On the other hand, the LITTM filtering process doesn't require any reference signal or a precise estimate of the fundamental frequency of the harmonic noise, and only approximate frequency band of the noise within the amplitude spectra is considered. The only required parameter of the method is the width of this frequency band in the spectral domain. The LITTM filter is first applied to synthetic data and then we analyze a real marine dataset to compare the quality of the output after removing the power line noise by classical notch, median and proposed LITTM filters. We observe that the power line harmonic noise is completely filtered out by LITTM filter, and unlike the conventional notch filter, without any damage on the available frequencies around the notch frequency band. It also provides a more balanced amplitude spectrum since it does not produce amplitude notches in the spectrum. [ABSTRACT FROM AUTHOR]

Combined digital filters are the basis of fault selection and identification in electric microprocessor protection. The commonly used combined digital filters based on wavelet transform cannot eliminate the interference components of traditional filter, resulting in low reliability of electric microcomputer protection. To this end, a design method of combined digital filter for electric microcomputer protection is proposed based on distributed algorithm. First, the combined digital filter and each implementation module are designed. Then, the principle of distributed algorithm is introduced, and realization of distributed algorithm is analysed, so as to realize the design of combined digital filter. The experimental results show that calculation of the filter designed by this method is simple and effective, and the development of electric microprocessor protection is promoted. [ABSTRACT FROM AUTHOR]

In this paper, a blocking-artifact detection method is proposed for motion-compensated frame-rate up-conversion (MC-FRUC) algorithms. In the MC-FRUC process, most of the notable blocking artifacts occur in unreliable motion-compensated regions. To find the unreliable motion-compensated regions, an occlusion detection (OD) method for which the neighboring motion vectors are used is applied. If an occlusion occurs, then the use of median filtering reduces any inappropriate motion-compensated errors; otherwise, the normal motion compensated interpolation (MCI) is applied. In addition, to reduce the occurrence of the blocking artifacts in the MC-FRUC algorithms, a blocking-artifact-reduction method for which the blocking-artifact strength in the frequency domain is applied to the occluded regions is utilized. The experiment results show that the proposed method shows more-favorable peak signal-to-noise ratio (PSNR) values compared with those of the conventional FRUC algorithms regarding full-HD (1920 × 1080) and WQXGA (2560 × 1600) sequences. [ABSTRACT FROM AUTHOR]

Noise reduction is a paramount preliminary step in many computer vision applications in which the presence of undesired noise can distort the results. Lately, the removal of high density salt and pepper noise, as a particular case of impulse noise, has experimented a peak of interest. In this paper, a novel filter, called the improved fuzzy mathematical morphology open-close filter (i-FMMOCS), is presented. This filter considerably improves the results obtained by the so-called fuzzy mathematical morphology open-close filter, through the use of some fuzzy mathematical operators, especially designed to avoid the use of the noisy pixels into the computations. A statistical analysis using some objective restoration measures and the visual comparison of the experimental results show that the proposed filter outperforms significantly several state-of-the-art filters for images corrupted from 5% up to 98% of salt and pepper noise. [ABSTRACT FROM AUTHOR]

A highly selective filter is designed, working at 1.55 µm and having a 3-dB bandwidth narrower than 0.4 nm, as is required in Dense Wavelength Division Multiplexed systems. Different solutions are proposed, involving photonic crystals made rectangular- or circular-section dielectric rods, or else of holes drilled in a dielectric bulk. The polarization and frequency selective properties are achieved by introducing a defect in the periodic structure. The device is studied by using in-house codes implementing the full-wave Fourier Modal Method. Practical guidelines about advantages and limits of the investigated solutions are given. [ABSTRACT FROM AUTHOR]

Non invasive feature detection in wood based application requires exact discrimination between geometrical edges and texture. It has been found that traditional edge detection algorithms are highly sensitive to noise and texture and produces inferior results with wood. The present work encompasses a micro level reconstruction of Palash and Rosewood by using microX-rays CT scanner. It also encompasses a new edge detection algorithm using newly constructed Chebyshev polynomial based fractional order differentiator. Transform based method has been used for reconstruction purpose. Newly designed fractional order filter has been applied on these reconstructed images. Chebyshev polynomial based fractional order differentiator has been used for filtering operation. Quadrature Mirror Filter (QMF) concept has been used for design of high pass filter and low pass filter. Preprocessing has been performed by using this filter. Canny edge detection algorithm has been used on this preprocessed image. The algorithm has been tested on two different test cases of wood images a) Palash and b) Rosewood. The effect of relaxation coefficient has also been presented and discussed. [ABSTRACT FROM AUTHOR]

Satellite's attitude can be determined by using several different ways. In order to use a recursive filter to determine the attitude especially after crucial intervals for the satellite including detumbling, eclipse, etc., single-frame methods can be used, and singular value decomposition (SVD) method has been selected because of its robustness for this paper. They can be placed for the initial values, or continuous input to the filter in addition to covariance matrix at each step. Also, sensor configurations depending on the position of the Sun are considered and used in the SVD method. Wahba's loss function is minimized with separating the basic matrix including the reference and model vectors into singular values because many researches show the SVD as the most robust algorithm after error analyses between several single-frame methods. Sun sensor, magnetometer, and horizon sensor are the selected common attitude sensors for small satellites in order to compare their attitude determination performances. For this purpose, absolute errors for different sensor configurations in the simulation environment in addition to the RMS errors are presented. The purpose of the paper is to present an attitude determination concept for a nanosatellite. Also, different sensor configurations are considered in the single-frame method with switching logic depending on the vector data. Horizon sensor and sun sensor are the optimum pair for the light side of the Earth on the other hand, during the eclipse; horizon sensor and magnetometer give the most accurate results. Study shows that the proposed algorithm can be performed for initial values to the Kalman filter, and in the transient phase before the filter tuned in practical satellite usage. In the eclipse period, sun-independent sensors are used and changing configurations provide better attitude estimation results to filtering techniques. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient implementation of the generalized labeled multi-Bernoulli (GLMB) filter by combining the prediction and update into a single step. In contrast to an earlier implementation that involves separate truncations in the prediction and update steps, the proposed implementation requires only one truncation procedure for each iteration. Furthermore, we propose an efficient algorithm for truncating the GLMB filtering density based on Gibbs sampling. The resulting implementation has a linear complexity in the number of measurements and quadratic in the number of hypothesized objects. [ABSTRACT FROM PUBLISHER]

In this paper, a coarse alignment method based on apparent gravitational motion is proposed. Due to the interference of the complex situations, the true observation vectors, which are calculated by the apparent gravity, are contaminated. The sources of the interference are analyzed in detail, and then a low-pass digital filter is designed in this paper for eliminating the high-frequency noise of the measurement observation vectors. To extract the effective observation vectors from the inertial sensors' outputs, a parameter recognition and vector reconstruction method are designed, where an adaptive Kalman filter is employed to estimate the unknown parameters. Furthermore, a robust filter, which is based on Huber's M-estimation theory, is developed for addressing the outliers of the measurement observation vectors due to the maneuver of the vehicle. A comprehensive experiment, which contains a simulation test and physical test, is designed to verify the performance of the proposed method, and the results show that the proposed method is equivalent to the popular apparent velocity method in swaying mode, but it is superior to the current methods while in moving mode when the strapdown inertial navigation system (SINS) is under entirely self-contained conditions. [ABSTRACT FROM AUTHOR]

This paper describes a novel image filter with superior performance on detail-preserving removal of random-valued impulse noise superimposed on natural gray-scale images. The non-local means filter is in the limelight as a way of Gaussian noise removal with superior performance on detail preservation. By referring the fundamental concept of the non-local means, we had proposed a non-local median filter as a specialized way for random-valued impulse noise removal so far. In the non-local processing, the output of a filter is calculated from pixels in blocks which are similar to the block centered at a pixel of interest. As a result, aggressive noise removal is conducted without destroying the detailed structures in an original image. However, the performance of non-local processing decreases enormously in the case of high noise occurrence probability. A cause of this problem is that the superimposed noise disturbs accurate calculation of the similarity between the blocks. To cope with this problem, we propose an improved non-local median filter which is robust to the high level of corruption by introducing a new similarity measure considering possibility of being the original signal. The effectiveness and validity of the proposed method are verified in a series of experiments using natural gray-scale images. [ABSTRACT FROM AUTHOR]

The problem of refinement of the quality of filtering of noisy audio signals with the help of the methods based on a discrete wavelet transform with real bases and a dual-tree (complex) wavelet transform using analytical wavelets as basis functions is considered. Test examples and processing of experimental data have shown that, in the case of the optimum selection of the threshold level, the approach using the dual-tree wavelet transform ensures the minimum signal reconstruction error after correction of wavelet coefficients. [ABSTRACT FROM AUTHOR]

Land cover classification using very high spatial resolution (VHSR) imaging plays a very important role in remote sensing applications. However, image noise usually reduces the classification accuracy of VHSR images. Image spatial filters have been recently adopted to improve VHSR image land cover classification. In this study, a new object-based image filter using topology and feature constraints is proposed, where an object is considered as a central object and has irregular shapes and various numbers of neighbors depending on the nature of the surroundings. First, multi-scale segmentation is used to generate a homogeneous image object and extract the corresponding vectors. Then, topology and feature constraints are proposed to select the adjacent objects, which present similar materials to the central object. Third, the feature of the central object is smoothed by the average of the selected objects' feature. This proposed approach is validated on three VHSR images, ranging from a fixed-wing aerial image to UAV images. The performance of the proposed approach is compared to a standard object-based approach (OO), object correlative index (OCI) spatial feature based method, a recursive filter (RF), and a rolling guided filter (RGF), and has shown a 6%-18% improvement in overall accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a modified GrabCut algorithm is proposed using a clustering technique to reduce image noise. GrabCut is an image segmentation method based on GraphCut starting with a user-specified bounding box around the object to be segmented. In the modified version, the original image is filtered using the median filter to reduce noise and then the quantized image using K-means algorithm is used for the normal GrabCut method for object segmentation. This new process showed that it improved the object segmentation performance a lot and the extract segmentation result compared to the standard method. [ABSTRACT FROM AUTHOR]

To obtain well-dehazed images at the receiver while sustaining low bit rates in the transmission pipeline, this paper investigates the effects of image dehazing methods using dehazing contrast-enhancement filters on image compression for surveillance systems. At first, this paper proposes a novel image dehazing method by using a new method of calculating the transmission function--namely, the direct denoising method. Next, we deduce the dehazing effects of the direct denoising method and image dehazing method based on dark channel prior (DCP) on image compression in terms of ringing artifacts and blocking artifacts. It can be concluded that the direct denoising method performs better than the DCP method for decompressed (reconstructed) images. We also improve the direct denoising method to obtain more desirable dehazed images with higher contrast, using the saliency map as the guidance image to modify the transmission function. Finally, we adjust the parameters of dehazing contrast-enhancement filters to obtain a corresponding composite peak signal-to-noise ratio (CPSNR) and blind image quality assessment (BIQA) of the decompressed images. Experimental results show that different filters have different effects on image compression. Moreover, our proposed dehazing method can strike a balance between image dehazing and image compression. [ABSTRACT FROM AUTHOR]

This paper presents a new method for designing digital recursive integrators and differentiators by using nonlinear stochastic global optimization based on particle swarm optimization (PSO). A modified PSO is used to optimize the unknown coefficients of second-order and third-order recursive integrators in order to obtain a better magnitude response closer to the ideal integrator. The coefficients of the state-of-the-art available filters in the literature are chosen as initial points in the PSO process. By choosing a good starting point, convergence to an optimal solution is greatly facilitated. A dynamic modification of the fitness function used in the PSO process leads to the design of a set of digital integrators each optimized for a specific frequency range. Then, second-order and third-order recursive digital differentiators are designed by inverting and stabilizing the transfer functions of the designed recursive integrators. The obtained stabilized differentiators are further optimized using PSO to further improve their performance. The magnitude responses of the designed filters outperform the existing integrators and differentiators. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Recently, for the recovery of images' processing history, passive forensics of possible manipulations has attracted wide interest. In particular, due to highly non-linearity, median filtering (MF) usually serves as an effective tool of counter forensic techniques for other image operations. Therefore, the importance of median filtering detection is self-evident. In this paper, through analysing the pixel differences of images, we found the indications to study the complex correlations introduced by median filtering and adopt two sets of describing features to measure them. More Specifically, we utilize a linear prediction model for the differences of image that is computed along a specific direction and estimate the prediction coefficients to construct a linear descriptor L. Besides, we make use of the histogram of rotation invariant local binary pattern (LBP) to form a nonlinear descriptor N. According to our observation, we also propose an enhanced feature EF to further improve the detection performance. Based on these, we present a novel median filtering detection scheme incorporating both the linear and nonlinear descriptors. Extensive experiments are carried out, which demonstrate that our proposed scheme gains favorable performance comparing to state-of-the-art methods, especially for low resolution images and JPEG compressed images, and shows resistance to noise attack. [ABSTRACT FROM AUTHOR]

SUMMARY In this paper, we propose an L1-approximation for the design of FIR digital filters with complex coefficients. The L1-approximation has the advantage of having a flatter passband and a small overshoot around the discontinuity point as compared with the L2-approximation and [ABSTRACT FROM AUTHOR]

This paper discusses the development of real-time simulation platform using digital signal processor (DSP) for photovoltaic (PV) system to study maximum power tracking algorithms in the laboratory. In this paper, PV module is simulated and deployed in TMS320F28335 to emulate the characteristics of PV at different temperature and irradiation with two DC voltage source. Further, maximum power point tracking (MPPT) of PV module with statistical method is developed. In order to evaluate the performance of the proposed MPPT control algorithm, the authors propose a real-time PV simulation system consisting of a PV module with a buck converter using a DSP and two DC voltage source to emulate the temperature and irradiation. Further, the proposed statistical MPPT is compared with the performance of the existing perturb and observe MPPT algorithm. Also, the performance of MPPT algorithms is tested with PV and a buck converter at different temperature and irradiation using hypothetical source. This scheme is validated with that of standard conditions given on the PV data sheet. This work may enable more researchers to study the integration of renewable energy sources and power electronics circuits at a low-cost without damaging the system. [ABSTRACT FROM AUTHOR]

Recommender systems (RSs) use information filtering to recommend information of interest (to a user). Similarly, personalisation can be adopted for recommendations in e-market. We propose a new and innovative system called as interest-based recommender system (IBRS) for personalisation of recommendations. The IBRS is an agent-based RS that takes into account user's preferences. It can transform a standard product (or service) into a dedicated solution for an individual. The system discovers interesting product alternatives based on user's underlying mental attitudes (likes and dislikes) during the repair process using argumentation. The proposed method combines a hybrid RS approach with automated argumentation-based reasoning between agents. The system improves results by improving the recommendation repair activity. We consider a book recommendation application, for experiment to carry out the system's (objective and subjective) evaluation using standard metrics. The experiments confirm that the proposed IBRS improves user's acceptance of the product as compared with a traditional hybrid method and an argumentation-enabled state-of-the-art recommendation method. The system has been found to be more effective than its traditional counterpart when dealing with the new user problems. [ABSTRACT FROM AUTHOR]

The paper presents a concept of an innovative interaction structure for a digital electric vehicle (EV) dashboard. The structure connects interactions between vehicle, driver and traffic infrastructure, in order to help users driving in a conscious way, informing them about their performances and providing tools able to modify driving behaviour. Through the Systemic Design approach, it is possible to move from a quantitative configuration (set on consumption) to a new one set on resource optimization. The achievement is a new layout for the information visualization system designed for an electric vehicle able to communicate to the driver the environmental impact of its drive style. [ABSTRACT FROM AUTHOR]

Processes in digital filters are analyzed with consideration for the effects of quantization at an arbitrary number of digits in the representation of numbers and overflow under periodic external influences. An analysis technique based on representation of stationary oscillations as an invariant set of nonlinear discrete point mappings is used. The spectral composition of the system response and nonlinear distortions of signals with an arbitrary period are calculated with the use of classical and modernized discrete Fourier transforms. The results of calculations of processes in digital bandpass Butterworth and Chebyshev filters are presented. The dependences of the nonlinear distortion coefficient on the encoding type, the number of digits in the representation of numbers, and the order of the digital filter are demonstrated. The influence of the number of digits on frequency responses of filters is determined. [ABSTRACT FROM AUTHOR]

This paper presents a novel voltage mode universal filter (UF) using digitally programmable current feedback amplifier. The proposed filter configuration uses only one input variable and realizes all the five filter functions at single output port only. Generation of all the filter functions (types) at the single output port is governed digitally The UF is fully programmable as all the filter functions (types) and their parameters are independently programmable. Other salient features of UF include full cascadability by virtue of appropriate input/output port impedance and use of two grounded capacitors only. [ABSTRACT FROM AUTHOR]

In this paper, a new structure is proposed to utilize the noise-shaping in a charge redistribution successive approximation register (SAR) analog-to-digital converter (ADC). The proposed ADC is based on the error-feedback structure and it does not require any extra capacitor compared to the main SAR ADC and just by employing an operational transconductance amplifier (OTA), a first-order noise-shaping is provided. The closed-loop configuration of the OTA is similar to the flip-around scheme in which the dummy capacitor also acts as the sampling capacitor. In this configuration, the quantization noise of the ADC is sampled and transferred via the dummy capacitor without any charge sharing or capacitor interleaving, and so, the capacitors mismatch is alleviated in the feedback path. The proposed ADC is realized by employing a few number of capacitors and switches compared to the conventional SAR ADC. As a design example, the proposed noise-shaping SAR ADC is simulated in a 90 nm CMOS technology by employing a 3-bit SAR ADC. Simulation results with Spectre-RF shows 11.1-bit effective resolution in 1 MHz input bandwidth and 128 MHz sampling rate while consuming 208 μW power. The achieved figure of merit is 46.4 fJ/conv-step. [ABSTRACT FROM AUTHOR]

In this paper, we study the performance of various models for automated evaluation of descriptive answers by using rank based feature selection filters for dimensionality reduction. We quantitatively analyze the best from amongst five rank based feature selection techniques, namely Chi Squared filter, Information Gain filter, Gain Ratio filter, Relief filter and Symmetrical Uncertainty filter. We use Sequential Minimal Optimization with Polynomial kernel to build models and we evaluate these models in terms of various parameters such as Accuracy, Time to build the models, Kappa, Mean Absolute Error and Root Mean Squared Error. For all except the Relief filter, the accuracies obtained are at least 4% better than the accuracies obtained with the same models without any filters applied. We found that the accuracies recorded are same for Chi Squared filter, Information Gain filter, Gain Ratio filter and Symmetrical Uncertainty filter. Therefore accuracy alone is not the sole determinant in selecting the best filter. The time taken to build the models, Kappa, Mean Absolute Error and Root Mean Squared Error play a major role in determining the effectiveness of these filters. The overall rank aggregation metric of Symmetrical Uncertainty filter is 45 and this is better by 1 rank than the rank aggregation metric of Information gain filter. Symmetric Uncertainty filter's rank aggregation metric is better by 3, 6, 112 ranks respectively when compared to the rank aggregation metrics of Chi Squared filter, Gain Ratio filter and Relief filters. Through these quantitative measurements, we conclude that Symmetrical Uncertainty attribute evaluation is the overall best performing rank based feature selection algorithm applicable for auto evaluation of descriptive answers. [ABSTRACT FROM AUTHOR]

We analyze a two-stage echo cancellation technique for on-channel repeaters (OCRs) based on the reconstruction of the coupling channel impulse response via digital filtering. The estimation of the coupling channel between the transmitting and the receiving antennas is achieved through the injection in the repeated signal of locally generated low-power pseudo-noise sequences or trains of short pulses. The analytical model developed in this paper permits the investigation of some important performance figures, such as the mean rejection ratio, the echo suppression and the echo suppression at nominal position. In addition, a new analytical framework dealing with canceller stability issues, arising due to the non perfect echo cancellation, is derived. Specifically, an upper bound on the probability of instability of the canceller is provided. As shown in the numerical results, this framework permits the identification of the main OCR design guidelines. Finally, we will validate our analytical models by showing their accordance with the experimental measurements realized with the OCR prototypes we developed. [ABSTRACT FROM AUTHOR]

This brief presents a new low-complexity reconfigurable fast filter bank (RFFB) for wireless communication applications such as spectrum sensing and channelization. In RFFB, the bandwidth and center frequency of sub-bands can be varied with high frequency resolution without hardware reimplementation. This is achieved with an improved modified frequency transformation-based variable digital filter (MFT-VDF) at the first stage of the proposed multistage implementation. Existing second-order frequency transformation-based low-pass VDFs have limited cutoff frequency range which is approximately 12.5% of the sampling frequency. The proposed low-pass MFT-VDF offers unabridged control over the cutoff frequency on a wide frequency range thereby, improving the cutoff frequency range of existing VDFs. The design example shows that the RFFB is easy to design and offers substantial savings in gate counts over other filter banks. [ABSTRACT FROM AUTHOR]

This paper focuses on the design problem of a recursive networked strong tracking filter (NSTF) for a class of nonlinear networked systems with parameter perturbations and unknown inputs. The sensors for the networked system are allowed to be spatially distributed in a large geographical area, and signals are transmitted via a shared communication channel with limited capacity. For this kind of system structure, the measurements from different sensors may experience probabilistic data loss with different probabilities. A series of Bernoulli sequences is employed to describe the multiple packet dropout rates. Parameter perturbations and unknown inputs in the system are considered in the filter design process. A recursive networked extended Kalman filter is first derived in the least mean square sense by taking the packet dropout phenomenon into account. Then, a fading factor is introduced in the filter structure in order to cope with the parameter perturbations and unknown system inputs, and a recursive NSTF is derived by developing the so-called networked orthogonal principle. It is shown that the proposed NSTF is capable of providing satisfactory estimation results even in the presence of system parameter perturbations and/or unknown system inputs. A simulation study is carried out on a practical Internet-based three-tank system, and the estimation results show the effectiveness and applicability of the proposed filtering techniques. [ABSTRACT FROM PUBLISHER]

The most commonly used intensity measure in ground-motion prediction equations is the pseudo-absolute response spectral acceleration (PSA), for response periods from 0.01 to 10 s (or frequencies from 0.1 to 100 Hz). PSAs are often derived from recorded ground motions, and these motions are usually filtered to remove high and low frequencies before the PSAs are computed. In this article we are only concerned with the removal of high frequencies. In modern digital recordings, this filtering corresponds at least to an anti-aliasing filter applied before conversion to digital values. Additional high-cut filtering is sometimes applied both to digital and to analog records to reduce high-frequency noise. Potential errors on the short-period (high-frequency) response spectral values are expected if the true ground motion has significant energy at frequencies above that of the anti-aliasing filter. This is especially important for areas where the instrumental sample rate and the associated anti-aliasing filter corner frequency (above which significant energy in the time series is removed) are low relative to the frequencies contained in the true ground motions. A ground-motion simulation study was conducted to investigate these effects and to develop guidance for defining the usable bandwidth for high-frequency PSA. The primary conclusion is that if the ratio of the maximum Fourier acceleration spectrum (FAS) to the FAS at a frequency $$f_{saa} $$ corresponding to the start of the anti-aliasing filter is more than about 10, then PSA for frequencies above $$f_{saa} $$ should be little affected by the recording process, because the ground-motion frequencies that control the response spectra will be less than $$f_{saa} $$ . A second topic of this article concerns the resampling of the digital acceleration time series to a higher sample rate often used in the computation of short-period PSA. We confirm previous findings that sinc-function interpolation is preferred to the standard practice of using linear time interpolation for the resampling. [ABSTRACT FROM AUTHOR]

This paper has developed two techniques to reduce the parasitic parameters and improve the high-frequency performance of the planar integrated electromagnetic interference (EMI) filter. First, each developed technique has been analyzed, respectively, then the performance of an EMI filter with both the developed techniques has been researched. The research contents are as follows. 1) Analyzing the improvement of the equivalent parallel capacitance (EPC) for a common mode (CM) EMI filter by two CM windings overlapped and interleaved layout. The EPC of the integrated EMI filter is about 14% of the reference EMI filter. 2) Analyzing the improvement of the equivalent series inductance (ESL) in the parallel branch for a CM EMI filter by each CM winding coupled with two ground winding layers. The resonance frequency brought by ESL is shifted to a higher frequency. At 30 MHz, the insertion loss is increased by 45 dB compared with the reference. In the mean time, the structure is equivalent to a two-stage L-type low-pass filter, which can largely increase the high-frequency attenuation compared with the one-stage L-type low-pass filter for the reference one. (3) Researching the performance of an EMI filter with both the proposed techniques. The developed EMI filter can not only decrease the EPC, but also reduce the negative effect of ESL. The developed EMI filter improves the high-frequency performance dramatically compared with the EMI filter with only one of the developed techniques. In the mean time, the differential mode (DM) capacitor is formed by the two overlapped and interleaved windings, and does not need an extra lumped DM capacitor. Therefore, CM inductors, CM capacitors, and DM capacitors can be integrated in the overlapped and interleaved L–C winding structure, so miniaturized EMI filter can be realized. The experiment results indicate effectiveness of the developed integrated EMI filters, and the cost and complexity is the same as the reference EMI filter. [ABSTRACT FROM PUBLISHER]

The objective of this article is to present an accurate model for behavioral modeling and digital predistortion of power amplifiers (PAs) using physical knowledge. Starting with the physically meaningful block model, we present a novel approach to simplify the block model and propose a simplified physical knowledge-based (SPK) model. The SPK model's performance was experimentally assessed by two types of PAs (a LDMOS Doherty PA and a GaN Doherty PA) and two signals (a single carrier 16QAM signal and a 2-carrier WCDMA signal). All experimental results prove the superiority of the SPK model. Compared with the 1st-dynamic deviation reduction (DDR) approach and the 2nd-simplified DDR approach, the SPK approach achieves average ACPR improvements of 4.4 dB and 2.5 dB, respectively. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE 23: 682-689, 2013. [ABSTRACT FROM AUTHOR]