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Objective: This study aimed to evaluate the significance of background noise in machine learning models assessing the GRBAS scale for voice disorders., Methods: A dataset of 1406 voice samples was collected from retrospective data, and a 5-layer 1D convolutional neural network (CNN) model was constructed using TensorFlow. The dataset was divided into training, validation, and test data. Gaussian noise was added to test samples at various intensities to assess the model's noise resilience. The model's performance was evaluated using accuracy, F1 score, and quadratic weighted Cohen's kappa score., Results: The model's performance on the GRBAS scale generally declined with increasing noise intensities. For the G scale, accuracy dropped from 70.9% (original) to 8.5% (at the highest noise), F1 score from 69.2% to 1.3%, and Cohen's kappa from 0.679 to 0.0. Similar declines were observed for the remaining RBAS components., Conclusion: The model's performance was affected by background noise, with substantial decreases in evaluation metrics as noise levels intensified. Future research should explore noise-tolerant techniques, such as data augmentation, to improve the model's noise resilience in real-world settings., Level of Evidence: This study evaluates a machine learning model using a single dataset without comparative controls. Given its non-comparative design and specific focus, it aligns with Level 4 evidence (Case-series) under the 2011 OCEBM guidelines Laryngoscope, 134:3537-3541, 2024., (© 2024 The Authors. The Laryngoscope published by Wiley Periodicals LLC on behalf of The American Laryngological, Rhinological and Otological Society, Inc.)

In the evolving domain of High Dynamic Range (HDR) display metrology, the precise definition and systematic characterization of input signals is important. Using input signals that include both spatially and temporally complex image sequences is beneficial to reflect properties of real‐world content as well as to cover corner cases. One challenge with using this kind of content is to verify if it is indeed suitable for the intended purpose. This paper introduces an automated framework employing a set of statistical measures to define and characterize content, which then can serve as an important steppingstone towards programmatic image sequences and testing workflows. [ABSTRACT FROM AUTHOR]

We propose deep learning‐enhanced self‐interference incoherent digital holography. Self‐interference incoherent digital holography is a hologram acquisition technique under the incoherent light condition, which can capture the real‐world complex hologram. To overcome unwanted optical defects of the self‐interference, we suggest a data‐driven approach for reducing the additional noise and enhancing the image quality. [ABSTRACT FROM AUTHOR]

1/f noise represents the dominant source of noise in the low‐frequency range in several physical systems, including field‐effect transistors. Its investigation can provide very important information on the fabrication process, highlighting the steps that are more prone to the introduction of defects. Here, 1/f noise in bilayer MoS2 transistors on paper with inkjet‐printed Ag contacts and hBN dielectric is investigated. These devices are promising building blocks for future low‐cost, flexible, and easily recyclable disposable electronics. The analysis of 1/f noise, performed following Hooge's empirical approach, results in a Hooge parameter ≈1–10, which is comparable to those reported for bilayer MoS2 transistors on SiO2. The present results indicate that the noise properties of the investigated devices are stable against substrate bending and are mainly determined by the printing of the dielectric, while not being sensibly affected by the use of the paper substrate. These results are promising for the further development of low noise 2D material‐based flexible electronics on paper. [ABSTRACT FROM AUTHOR]

A full‐panel circuit model of the on‐cell touch AMOLED is introduced to simulate the mutual interference between touch and display operations. The proposed panel model successfully reproduced nonlinear behaviors of the display noise observed in real systems. Also, the reverse‐directional interference, i.e., touch‐to‐display coupling, was simulated, showing that touch stimulation incurs the fluctuation of display charging voltages, possibly causing perceivable line defects. The proposed panel model can be used for various touch/display algorithms to reduce the interference effects and to determine key design parameters for new panels. [ABSTRACT FROM AUTHOR]

The sensitivity of the auditory system is regulated via two major efferent pathways: the medial olivocochlear system that connects to the outer hair cells, and by the middle ear muscles-the tensor tympani and stapedius. The role of the former system in suppressing otoacoustic emissions has been extensively studied, but that of the complementary network has not. In studies of selective attention, decreases in otoacoustic emissions from contralateral stimulation have been ascribed to the medial olivocochlear system, but the acknowledged problem is that the results can be confounded by parallel muscle activity. Here, the potential role of the muscle system is examined through a wide but not exhaustive review of the selective attention literature, and the unifying hypothesis is made that the prominent "physiological noise" detected in such experiments, which is reduced during attention, is the sound produced by the muscles in proximity to the ear-including the middle ear muscles. All muscles produce low-frequency sound during contraction, but the implications for selective attention experiments-in which muscles near the ear are likely to be active-have not been adequately considered. This review and synthesis suggests that selective attention may reduce physiological noise in the ear canal by reducing the activity of muscles close to the ear. Indeed, such an experiment has already been done, but the significance of its findings have not been widely appreciated. Further sets of experiments are needed in this area., (© 2021 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.)

Machine acoustics is an important area of research impacting the quality and comfort of human life. With increased levels of electrification and the wider use of electric motors, the contribution of motor drives towards quieter acoustic systems becomes increasingly important. This paper presents a novel acoustic improvement method involving the use of acoustic waves generated from High Frequency Injection to perform Active Noise Control. Although High Frequency Injection has been used widely in the domain of sensorless motor control, its acoustic generation process has been so far perceived as a negative by‐product. This paper presents the analysis and experimental results from the application of the proposed method to the Helicopter Electro‐Mechanical Actuation System. Considering the extensive use of motor drives in a number of industries, the proposed practice of High Frequency Injection Active Noise Control can have a significant impact to future applications. [ABSTRACT FROM AUTHOR]

A general quantum noisy channel is analyzed, wherein the transmitted qubits may experience symmetrybreaking decoherence, along with memory effects. We examine generalized Bellbasis and find that the optimal basis is not the fully entangled one, but a combination of factorized and partiallyentangled states in the presence of memory, asymmetry and the statebias of the noise. Capacitymaximization is shown to be achievable by combining temporal shaping of the transmitted qubits and optimal basis selection. [ABSTRACT FROM AUTHOR]

Signal‐to‐noise ratio and spatial resolution are quantitatively analysed in the context of in‐line (propagation based) X‐ray phase‐contrast imaging. It is known that free‐space propagation of a coherent X‐ray beam from the imaged object to the detector plane, followed by phase retrieval in accordance with Paganin's method, can increase the signal‐to‐noise in the resultant images without deteriorating the spatial resolution. This results in violation of the noise‐resolution uncertainty principle and demonstrates 'unreasonable' effectiveness of the method. On the other hand, when the process of free‐space propagation is performed in software, using the detected intensity distribution in the object plane, it cannot reproduce the same effectiveness, due to the amplification of photon shot noise. Here, it is shown that the performance of Paganin's method is determined by just two dimensionless parameters: the Fresnel number and the ratio of the real decrement to the imaginary part of the refractive index of the imaged object. The relevant theoretical analysis is performed first, followed by computer simulations and then by a brief test using experimental images collected at a synchrotron beamline. More extensive experimental tests will be presented in the second part of this paper. [ABSTRACT FROM AUTHOR]

This paper considers the determination of the frequency of a sinusoidal signal from its sampled values. A method is described by which the effect of the noise is reduced and the frequency is determined accurately. The method forms the sample set composed of four samples from the signal with unknown frequency, and the binary representation of the estimation is determined successively by varying the sampling frequency. However, the noise in the signal may produce an error. One means to eliminate the effect of the noise is to determine one bit of the binary number based on several sample sets. This paper proposes the following method to reduce the estimation error for the frequency due to the noise. The binary number is partitioned into the upper and lower bits. The upper bits are determined by the property of the rum, and the lower bits are determined by the property of the ramdom-walk. In either case, each bit is determined by several sample sets. By the evaluation based on the bit error rate, the accuracy is improved by combining the forementiomed methods, compared with the majority decision. A comprehensive evaluation was also made by simulation, indicating that the r.m.s. error can be reduced to 2 percent for the signal-to-noise ratio of 20 dB. [ABSTRACT FROM AUTHOR]

This article is a guest editorial that discusses advancements and future trends in noise radar technology. Noise radar technology uses random and non-periodic radar signals to eliminate ambiguities present in other radars. The article explores the practical aspects of noise radar technology, such as evaluating the degree of randomness in transmission and the computational load of signal processing. It also covers topics like electronic warfare, anti-intercept features, and the potential applications of artificial intelligence in noise radar technology. The article includes specific papers on implementation aspects, waveform selection, anti-intercept features, and artificial intelligence applications in noise radar technology. The authors hope that this special issue provides valuable insights into the advancements and future trends of noise radar technology. [Extracted from the article]

This paper studies the autoregressive and moving average (ARMA) model with time‐functional variance (TFV) noises, called the ARMA‐TFV model. We first establish the consistency and asymptotic normality of its least squares estimator (LSE). The Wald tests and portmanteau tests are constructed based on the theory for variable selection and model checking. A simulation study is carried out to assess the performance of our approach in finite samples, and two real examples are given. It should be mentioned that the process generated from the ARMA‐TFV model is not stationary, and the technique in this paper is nonstandard and may provide insights for future research in this area. [ABSTRACT FROM AUTHOR]

Communication systems are greatly hampered by many disruptive noises in powerline communication systems (PLC), which come with strong interference, resulting in the malfunction of PLC systems. Hence, there is a need to model noise and its effect on communication systems. This paper presents noise modelling and mitigation techniques for indoor broadband powerline communication systems. To model the PLC noise, frequency domain measurements employing the GSP‐930 spectrum analyser were carried out to determine the noise frequency response in the frequency range of 1–30 MHz. The results obtained were plotted. While the analytical model for the noise model is presented, furthermore, noise mitigation techniques for multiple input multiple output PLC (MIMO‐PLC) systems in the form of spatial modulation PLC systems have been proposed. The SM‐PLC system employs the indices of the individual transmit lines to increase the data rate, as opposed to the traditional MIMO‐PLC systems, where the symbol to be transmitted is transmitted by duplicating the symbol across all lines. The proposed system uses the maximum likelihood (ML) detector at the receiver to obtain estimates of the transmitted symbols. The simulation results of the SM‐PLC system are compared with the already existing MIMO‐PLC system and show a significant improvement of ≈6 dB and 5.2 dB in signal‐to‐noise ratio (SNR) at a bit error rate of 10(−5) for spectral efficiencies of 4 bits per channel use (bpcu) and 6 bpcu, respectively. On comparison of the SM‐PLC system having a combination of additive white Gaussian noise and impulse noise at the receiver, the SM‐PLC system outperformed the traditional MIMO‐PLC by 3.5 and 3.8 dB in SNR for 4 and 6 bpcu, respectively. [ABSTRACT FROM AUTHOR]

Summary: This paper introduces four proposals to enhance physical layer security (PLS) in low Earth orbit (LEO) satellite systems. The first proposal leverages the Alamouti code aided by artificial noise (AN) and involves the collaborative use of two LEO satellites, ensuring secure downlink transmission. Its efficiency is further enhanced when implementing a power‐balanced Alamouti code. The second PLS proposal capitalizes on an reconfigurable intelligent surface (RIS) to introduce interference to potential eavesdroppers. As the RIS manages the reflected channel, this security measure is achieved without necessitating additional transmit power or receiver operations. The third proposal integrates the first and second solutions, resulting in improved secrecy rates compared to the individual proposals, nearly reaching the maximum achievable rate. The fourth proposal is based on a relay‐based method, securing all transmission links from the satellite to the relay and from the satellite and relay to the legitimate user. The secrecy performance simulation results presented in the paper demonstrate the remarkable effectiveness of the proposed solutions. [ABSTRACT FROM AUTHOR]

This paper addresses the state estimation problem for a class of two‐dimensional shift‐varying systems with time‐correlated multiplicative measurement noises and additive noises. The time‐correlated multiplicative noises can be described as a linear system model corrupted by white noise. The main objective of this paper is to propose a recursive iterative coupled new‐type estimators and design the estimated gain reasonably to guarantee the minimum error covariance at each step. First, two new‐type coupling estimators are designed by introducing a new term. The unbiasedness of the two estimators are guaranteed by resorting to the mathematical inductive approach. Subsequently, an effective estimation is proposed given initial conditions. Moreover, the boundedness performance is investigated of the error covariance, and an upper bound is given based on the spectral norm. Finally, two numerical example are presented as an example to show the effectiveness of the estimation algorithm. [ABSTRACT FROM AUTHOR]

This paper presents a 30–36 GHz limiter low‐noise amplifier (limiter‐LNA) MMIC for high power and high mobility millimeter‐wave radar systems. The PIN‐diode limiter network and the LNA are codesigned to realize high input‐power handling capability, good small‐signal performance, and small chip area. A two‐state matching capacitor is presented to improve both the input‐power handling capability at the high input‐power level and the input return loss at the small‐signal level. The proposed circuit is fabricated with a combined PIN/0.15‐µm‐GaAs‐pHEMT process. The limiter‐LNA is capable of handling 39 dBm continuous wave (CW) input‐power without failure with only two limiter stages. The measured noise figure is 1.8–2.5 dB, the small‐signal gain is 18.5 ± 0.5 dB, the output power at 1 dB compression point is larger than 11 dBm, and the dc power consumption is 72 mW. The chip area, including testing pads, is only 2.1 mm × 1.0 mm. This limiter‐LNA MMIC is believed to have the highest input‐power handling capability and smallest chip area among limiter‐LNA MMICs at this frequency range reported up to date. [ABSTRACT FROM AUTHOR]

In the field of optoelectronic tracking, precisely modeling the motion equations of the tracked target is often challenging, and in some cases, they may even be entirely unknown. This necessitates the use of a robust state estimator for accurate state estimation. Additionally, atmospheric turbulence, variations in illumination, and intricate observation backgrounds may introduce a significant increase in observation noise for the tracked target. To address these challenges, one approach is to introduce adaptive factors, such as the Mahalanobis method, into the robust state estimator to enhance estimation accuracy. However, further exploration has revealed that adaptive factors designed using different methods offer unique advantages in scenarios with varying levels of noise amplification. In this paper, different adaptive factors are further combined using an interacting multiple model approach, allowing the designed state estimator to exhibit stronger adaptability to noise amplification. The stability and effectiveness of this algorithm are validated through program simulations, double reflection mirror experiment, and drone trace prediction, demonstrating its applicability and reliability in diverse scenarios. [ABSTRACT FROM AUTHOR]

Summary: The paper analyzes the detection and estimation of multiple level shifts regardless of the order of integration of the time series. We show that it is possible to extend the Bai‐Perron methodology (1998) to the I(1) and NI(1) nonstationary cases so that a unified framework to test for the presence of multiple level shifts in a robust way is designed. The finite sample performance of the proposed statistics is carried out, establishing a comparison with other existing approaches in the literature. The paper illustrates the implementation of the statistics focusing on the real exchange rate with time series that either cover a long time period or provide a worldwide analysis. Robust detection of multiple level shifts is of great importance to define the statistical approach that is used to test the purchasing power parity hypothesis. [ABSTRACT FROM AUTHOR]

The aim of the present paper is to provide necessary and sufficient conditions to maintain a stochastic coupled system with porous media components and gradient‐type noise in a prescribed set of constraints by using internal controls. This work is a complementary contribution to the results obtained by the same authors, also on the viability problem associated to the porous media equation, but with Lipschitz noise. Second, the present paper provides a different framework in which the quasi‐tangency condition can be obtained with optimal speed. In comparison with the aforementioned result, and from a technical point of view, here, we transform the stochastic system into a random‐PDE one, via the rescaling approach, and then we study the viability of random sets. As an application, (stronger) conditions for the stabilization of the stochastic porous media equations are obtained. These are illustrated on a simple example. [ABSTRACT FROM AUTHOR]

In binocular stereo matching, there has been a problem of low matching accuracy and noise immunity in discontinuous regions and weak‐textured regions. This paper proposes a stereo matching algorithm based on an improved adaptive support window. In the cost computation stage, first, according to the preset arm length and colour threshold, a cross‐based arm is obtained, which centres on the pixel to be matched; then the adaptive regions of the vertical arm and the horizontal arm are constructed respectively, which have different shape and size. Finally, the union of the two adaptive regions is used as the final support window of Census transform. Performance evaluations on Middlebury stereo data sets demonstrate that the proposed algorithm outperforms other seven most challenging stereo matching algorithms. The mismatching rate of this algorithm is greatly reduced, and the anti‐noise performance is also improved considerably. Because the construction of the adaptive region is based on strict criteria and comprehensive consideration, the algorithm proposed in the paper can improve the matching accuracy in the weak‐textured regions and discontinuous disparity regions. [ABSTRACT FROM AUTHOR]

In engineering fields, time‐varying matrix inversion (TVMI) issue is often encountered. Zeroing neural network (ZNN) has been extensively employed to resolve the TVMI problem. Nevertheless, the original ZNN (OZNN) and the integral‐enhanced ZNN (IEZNN) usually fail to deal with the TVMI problem under unbounded noises, such as linear noises. Therefore, a neural network model that can handle the TVMI under linear noise interference is urgently needed. This paper develops a double integral‐enhanced ZNN (DIEZNN) model based on a novel integral‐type design formula with inherent linear‐noise tolerance. Moreover, its convergence and robustness are verified by derivation strictly. For comparison and verification, the OZNN and the IEZNN models are adopted to resolve the TVMI under multiple identical noise environments. The experiments proved that the DIEZNN model has excellent advantages in solving TVMI problems under linear noises. In general, the DIEZNN model is an innovative work and is proposed for the first time. Satisfyingly, the errors of DIEZNN are always less than 1 × 10−3 under linear noises, whereas the error norms of OZNN and IEZNN models are not convergent to zero. In addition, these models are applied to the control of the controllable permanent magnet synchronous motor chaotic system to indicate the superiority of the DIEZNN. [ABSTRACT FROM AUTHOR]

Wireless signals are commonly subject to diverse and complex noise interference. The typical assumption of Gaussian white noise often oversimplifies the noise, resulting in reduced accuracy in estimating the direction of arrival (DOA), especially in complex scenarios. To tackle this issue, this paper introduces a new Bayesian model for off‐grid DOA estimation. This model utilizes Gaussian mixture model (GMM)‐based Dirichlet processes (DP) to characterize noise, allowing adaptive adjustments in the number of Gaussian mixture models. Leveraging the factor graph representation of the Bayesian model, a low‐complexity mixed messaging passing algorithm, employing generalized approximate message passing (GAMP) and mean field (MF), is proposed. Simulation results validate the efficacy of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a robust watermarking method against high‐density salt and pepper noise attacks. Automatic region of interest (ROI) detection, embedding encoded data, removing different densities of noise, data extraction by omitting, and labeling the noisy pixels of Region of Non‐Interest (RONI), and decoding the extracted data using ROI pixel information as a key, are various steps of the presented scheme. The automatic ROI detection method separates the RONI from ROI with four vertices of the smallest rectangle, for the embedding process. The encoded watermark data is embedded into the least significant bits of RONI in four neighbour pixels. Adaptive Removal of high‐density Salt and pepper Noise method can enhance image quality and reduce the effect of salt and pepper noise attacks. The embedded information is preserved from destruction if the host image is impaired through the power of robustness. The best results are obtained through the action of extracting the watermark from RONI pixels, utilizing the same ROI detection method. Omitting and labeling the noisy pixels of the RONI will ensure healthy extracted watermark data, leading to decreased Bit Error Rate (BER) values. Finally, these data are interpreted using the key of ROI pixels, and the watermark data is decoded and retrieved. Due to salt and pepper noise obliterating pixel bits and their corresponding transform coefficients in the transform domain, the spatial domain is employed to enhance robustness against such attacks. The results show the high performance of the presented scheme. The average BER value for five MRI databases in a 97% salt and pepper noise attack is 38.6. [ABSTRACT FROM AUTHOR]

In this paper, we consider an explicit fully‐discrete approximation of the Cahn–Hilliard–Cook (CHC) equation with additive noise, performed by a standard finite element method in space and a kind of nonlinearity‐tamed Euler scheme in time. The main result in this paper establishes strong convergence rates of the proposed scheme. The key ingredient in the proof of our main result is to employ uniform moment bounds for the numerical approximations. To the best of our knowledge, the main contribution of this work is the first result in the literature which establishes strong convergence for an explicit fully‐discrete finite element approximation of the CHC equation. Finally, numerical results are finally reported to confirm the previous theoretical findings. [ABSTRACT FROM AUTHOR]

The architectures of many state‐of‐the‐art local tempering detection models are complexity, and the training process of those models is also time‐consuming. Therefore, this paper constructs a lightweight local tampering detection method based on the convolutional network MobileNetV2 and a dual‐stream network. Specifically, the algorithm first improves the MobileNetv2, which not only reduces the multiple of its downsampling operator to retain richer traces of image tampering, but also introduces the dilated convolution in it to expand the receptive field of feature maps. The dual‐stream network uses RGB stream to extract image tampering features such as strong contrast difference and unnatural tampered boundaries, and implements spatial rich model (SRM) stream to extract image tampered area and noise features of real area. Finally, the features extracted from two streams are fused through an improved attention mechanism called parallel convolutional block attention module (CBAM), which can improve the sensitivity of the model to important features in RGB and SRM. The experimental results show that the proposed algorithm still has higher positioning accuracy than some existing algorithms, while achieving lightweight. [ABSTRACT FROM AUTHOR]

Medical diagnostics rely heavily on ultrasound imaging since it is non‐invasive, inexpensive, and able to provide images in real time. However, the inherent existence of a kind of signal‐dependent noise in these images diminishes the use of ultrasound imaging systems. Speckle noise is inherently present in ultrasound images. Its inherent presence occurs during the image acquisition phase. It decreases the diagnostic usefulness of this imaging modality since it interferes with and reduces the image resolution and contrast. Speckle noise is multiplicative in nature. This multiplicative nature of speckle noise causes adverse effects on ultrasound imaging because it distorts the image quality and causes a loss of the patient's informative content in ultrasound imaging. This causes difficulty in tissue characterization. A lot of research has been done in this field to remove speckle noise while preserving medical information in the image. To handle this issue, research has been grouped into multiple domains. The two main domains include homomorphic and non‐homomorphic filtering. The homomorphic filtering uses a logarithmic transform that converts this multiplicative nature into an additive nature and uses any additive image restoration model to do a despeckling task. Non‐homomorphic filtering encompasses all methods that do not employ a logarithmic transform. Since the presence of speckle noise in ultrasound imaging is an inherent property. Therefore, the despeckling of medical ultrasound images is a mandatory task that cannot be avoided or ignored. This paper proposes a two‐step hybrid and homomorphic despeckling technique, where modified total variation method is applied as step one for speckle reduction purposes. Step two implements method of noise thresholding in the non‐subsampled contourlet transform (NSCT) domain using the bivariate shrinkage rule for edge preservation. The effectiveness and reliability of the proposed method are tested by comparing it with some of the latest methods based on qualitative and quantitative analyses. This paper will help the new researchers understand various problems and their solutions related to ultrasound image despeckling. [ABSTRACT FROM AUTHOR]

Use of Pulse Width Modulation (PWM) techniques has enabled the converters to be used in low‐frequency high‐power applications. The main objectives of PWM are to reduce the line current harmonic, switching energy loss, and torque pulsation and motor acoustic noise (for motor drive applications). This paper mainly deals with selective harmonic elimination PWM (SHEPWM), Hysteresis current controlled PWM (HCPWM), space vector PWM (SVPWM), bus‐clamping PWM (BCPWM), and the most advanced wavelet PWM technique (WPWM). Different conventional as well as advanced soft computing techniques have been discussed for SHEPWM in order to solve the complex non‐linear transcendental equations and obtain the optimized switching angles. The paper also deals with different conventional and advanced bus clamping sequences that have shown superior result in mitigating the switching loss. In order to judge the true performance of SHEPWM and CSVPWM in terms of accuracy of obtaining the switching angles, convergence rate, THD, torque ripple, switching energy loss, etc., a common experimental test bench consisting of three‐phase, two‐level, six switch inverter coupled with a 2 hp, 50 Hz, three‐phase induction machine has been formed. The selected BIA‐based SHEPWM and CSVPWM have been implemented in the MATLAB simulation software, and the same has also been applied to the experimental test bench through dSPACE 1104 DAC card. Performance of HCPWM and different BC‐PWM sequences has also been verified using the same experimental test bench. This manuscript will help the researches and practitioners working in this field, to gain a clear idea about the type of PWM to be used for their specific application in order to achieve superior performance. [ABSTRACT FROM AUTHOR]

The article presents the response of A. M. Reinhorn, G. Maddaloni, and K. P. Ryu on their study on the simulation of floor response spectra in shake tables. The authors clarified that floor amplification could be represented by functions related to the floor elevation. It mentions that the design of the test frame for the ceilings were illustrated to control the response in a test specimen using shake tables. It adds that oil column, noise, and seismic mass were indicated in a system diagram.

Many systems in the real world are periodic due to periodic phenomena in nature. Periodic hybrid stochastic differential equations are often used to model them. In many situations, it is inappropriate to study whether the solutions of periodic hybrid stochastic differential equations will converge to an equilibrium state (say, 0 or the trivial solution) but more appropriate to discuss whether the probability distributions of the solutions will converge to a stationary distribution, known as stability in distribution. This paper aims to determine whether or not a periodic stochastic state feedback control can make a given nonlinear periodic hybrid differential equation, which is not stable in distribution, to become stable in distribution. This problem will be referred to as stabilisation in distribution by periodic noise. There is little known on this problem so far. This paper initiates the study in this direction. [ABSTRACT FROM AUTHOR]

To improve the uniformity of one‐pixel width and continuity of the thinned edges, this paper proposes an edge thinning algorithm acting on grey‐scale edge images based on 24 self‐defined single‐pixel connection patterns. First, for binary or blurred grey‐scale gradient edge images, a distance–greyscale coupling algorithm is proposed to achieve gradient enhancement in the edge width direction. Then the elimination rules of noise points and gradient calculation method are given. Secondly, the marking rules of the first three pixels of each edge are given. The next pixel to be marked must meet that the new last three pixels belong to the 24 connection modes. Whether the qualified pixels are retained depends on its grey value and the local edge gradient. The algorithm is tested on four types of images. The results show that the proposed method can guarantee uniform, smooth, and connected one‐pixel‐wide lines that lie at the centre of the initial edges. The algorithm and the existing algorithms are performed on portrait image and four scenarios of the indoor datasets. Five evaluation indicators are statistically analyzed to prove the feasibility and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper is concerned with the optimal H2 filtering problem for continuous‐time systems with multiplicative noise and multiple sampled delay measurements. The reorganized observation technique is firstly applied for treating the sampled delay terms, and then an equivalent delay‐free sampled measurement is received. An optimal H2 filter is constructed by using a dynamic model with finite jumps, which can provide the state estimation of the measurement sampling interval as well as the measurement sampling moments. The filter gain is given in terms of the stabilizing solution to a set of specific Riccati differential equations. It should be pointed out that no state augmentation is required, and thus the Riccati equation developed in this paper remain the same dimension as that of the original system state. This is the clear distinction from the state augmentation method. A practical example is finally supplied to illustrate the efficiency of the proposed results. [ABSTRACT FROM AUTHOR]

Noise is inevitable when acquiring seismic data, and effective random noise attenuation is crucial for seismic data processing and interpretation. Training and inferencing two‐stage deep learning‐based denoising methods typically require massive noisy–clean or noisy–noisy pairs to train the network. In this paper, we propose an unsupervised seismic data denoising framework called a re‐visible blind block network. It is a training‐as‐inferencing one‐stage method and utilizes only single noisy data for denoising, thereby eliminating the effort to prepare training data pairs. First, we introduce a global masker and a corresponding mask mapper to obtain the denoised result containing all blind block information, enabling simultaneous optimization of all blind blocks via the loss function. The global masker consists of two complementary block‐wise masks. It is utilized to mask noisy data to obtain two corrupted data, which are then input into the denoising network for noise attenuation. The mask mapper samples the value of blind blocks in the denoised data and projects it onto the same channel to gather the denoised results of all blind blocks together. Second, the original noisy data are incorporated into the network training process to prevent information loss, and a hybrid loss function is employed for updating the network parameters. Synthetic and field seismic data experiments demonstrate that our proposed method can protect seismic signals while suppressing random noise compared with traditional methods and several state‐of‐the‐art unsupervised deep learning denoising techniques. [ABSTRACT FROM AUTHOR]

In the context of rock material and modeling uncertainties, the optimization of rock tunnel support systems is often conducted by selecting the most cost‐effective solution among several feasible options that typically rely on the engineer's experience, potentially leading to overlooking the most optimal design. To improve such a limitation, this paper presents a multi‐objective reliability‐based robust design, considering the cost, safety, and design robustness systematically while maintaining the computational efficiency. In this framework, the uncertainty‐based reliability constrains is performed using the first‐order reliability method (FORM) and an improved Hasofer–Lind–Rackwits–Fiessler recursive algorithm (iHLRF‐x). The design robustness, in terms of sensitivity index (SI), is evaluated using the normalized gradient of the system response to the noise factors, which can be efficiently obtained from the output of FORM analysis. Then, the Pareto front revealing the tradeoff between multiple objectives can be directly generated using the proposed optimization framework. To illustrate the effectiveness of this procedure, a set of the optimal design combinations of the shotcrete thickness and installation position for the exampled rock tunnel are obtained, and new perspectives pertaining the success of the reliability‐based robust designs are provided. [ABSTRACT FROM AUTHOR]

In this paper, we propose an anisotropic diffusion equation based on fractional‐order tensor diffusion applied on noisy images. We start by investigating the existence and uniqueness results of the proposed model. We also provide a discretization scheme based on the finite difference method. In order to prove the efficacy of our proposed approach, we deliver some simulations, which show robustness and remarkable results against noise while preserving edges and corners, compared to some well‐known models in literature. For a fair comparison, we manage to obtain the optimal parameters of every model thanks to PSNR and SSIM. We demonstrate the robustness efficacy of our model against high level of noise. [ABSTRACT FROM AUTHOR]

Small noise problems are quite important for all types of stochastic differential equations. In this paper, we focus on rough differential equations driven by scaled fractional Brownian rough path with Hurst parameter H∈(1/4,1/2]$H\in (1/4, 1/2]$. We prove a moderate deviation principle for this equation as the scale parameter tends to zero. [ABSTRACT FROM AUTHOR]

Dynamic vision sensor (DVS) imaging quality is significantly affected by pixel noise and temporal contrast (TC), which is inversely proportional to sensitivity. To reduce the noise event rate and improve sensitivity in bright‐light conditions in the DVS pixel circuit, this paper proposes improvements to the conventional DVS pixel circuit. The proposed DVS pixel circuit adopts stacked medium‐threshold transistors instead of a single high‐threshold transistor in the photoreceptor and introduces a threshold switching circuit. Compared with the conventional DVS pixel circuit, this design increases event threshold normalized by root mean square (RMS) noise voltage, reducing the dim‐light noise bandwidth. Additionally, it achieves higher sensitivity in bright‐light conditions compared with dim‐light conditions. The proposed DVS pixel circuit is implemented in a 110‐nm complementary metal‐oxide semiconductor (CMOS) process. Post‐simulation results show that, for photocurrents between 5 fA and 100 pA, the proposed DVS pixel circuit achieves a 35 Hz peak event rate at 15% TC, which is reduced to 3.1% of the conventional structure. For photocurrents exceeding 30 pA, the proposed structure can switch TC from 15% to 5%, maintaining a noise event rate below 0.1 Hz. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we use the maximum likelihood principle and the negative gradient search principle to study the identification issues of the multivariate equation‐error systems whose outputs are contaminated by an moving average noise process. The model decomposition technique is used to decompose the system into several regressive identification subsystems based on the number of the outputs. In order to improve the parameter estimation accuracy, a decomposition‐based multivariate maximum likelihood gradient iterative algorithm is proposed by means of the maximum likelihood principle and the iterative identification method. The numerical simulation example indicates that the proposed method has better parameter estimation results than the compared decomposition‐based multivariate maximum likelihood gradient algorithm. [ABSTRACT FROM AUTHOR]

In this paper, the problem of fault prognosis is investigated for linear stochastic systems with intermittent faults (IFs) and strong noise. Different from permanent faults, the degradation state of IFs are related to the fault duration time, leading to difficulties in the first step of fault prognosis, that is, the health indicator (HI) extraction. Generally, HI extraction of IFs is achieved by fault detection techniques. Therefore, the proposed fault prognosis approach mainly covers the following steps. First, the HI and degradation model are introduced for linear stochastic systems with IFs. Then, considering dynamic characteristic of systems and influence of strong noise, an IF detection algorithm under strong noise is proposed using weighted moving average methods to extract the HI. Moreover, an alternative HI extraction approach is given by an HI estimation way, which avoids using fault detection techniques. Subsequently, the degradation model is fitted by virtue of HIs and the least square method, and the remaining useful life is predicted with the aid of the obtained model. Finally, an experiment concerning the rotary steerable drilling tool system is provided to verify the effectiveness of the derived results. [ABSTRACT FROM AUTHOR]

The basic assumption of low‐rank methods is that noise‐free seismic data can be represented as a low‐rank matrix. Effective noise reduction can be achieved through the low‐rank approximation of Hankel matrices composed of the data. However, selecting the appropriate rank parameter and avoiding expensive singular value decomposition are two challenges that have limited the practical application of this method. In this paper, we first propose symplectic geometric decomposition that avoids singular value decomposition. The symplectic similarity transformation preserves the essence of the original time sequence as well as the signal's basic characteristics and maintains the approximation of the Hankel matrix. To select an appropriate rank, we construct the symplectic geometric entropy according to the distribution of eigenvalues and search for high‐contributing eigenvalues to determine the needed rank parameter. Therefore, we provide an adaptive approach to selecting the rank parameter by the symplectic geometric entropy method. The synthetic examples and field data results show that our method significantly improves the computational efficiency while adaptively retaining more effective signals in complex structures. Therefore, this method has practical application value. [ABSTRACT FROM AUTHOR]

The urban radio‐frequency (RF) noise generated by our cities continues to change with time. Although models exist to describe the RF noise as functions of frequency and urban land use types, very few models describe the spatial character or structure of the noise on the scales of city blocks (50–150 m). The goal of this work is to investigate the connection between urban morphology and the higher‐order spatial statistics of the noise field. To achieve this goal, a large measurement campaign was conducted in Boston, Massachusetts. Many spatial measurements allowed for calculation of spatial correlation functions of noise power in three different neighborhoods, which were used to quantify the spatial structure of the fields. A statistical point source model is then developed, with adjustable parameters relating to urban morphology. Good agreement between the model and the experimental correlation functions suggests the 25 MHz urban noise field is well described by a random network of fixed point sources, radiating with a 1/r power law behavior. Plain Language Summary: Our modern cities are filled with electronic devices. Each device can emit radiation and contribute to what is called the urban radio‐frequency noise field. The noise field is the combined effect from all these devices. If the noise field is strong enough it can negatively impact wireless communication, and the use of other electric devices. It is important to better understand the nature of the noise field in order to mitigate and plan for its negative effects. This paper describes in detail how the noise field is distributed in space, or its spatial structure. A theoretical model or tool is developed to help predict how the noise field looks spatially. Key Points: Radio‐frequency noise spatial correlation functions were calculated for three different neighborhoods in Boston, MassachusettsGood theoretical agreement suggests the noise field is well described by a random network of point sources radiating with a 1/r behavior [ABSTRACT FROM AUTHOR]

This paper applies the state derivative feedback method and proportional plus derivative state feedback method to design the fuzzy controllers for the nonlinear singular systems with external noises. The Takagi‐Sugeno fuzzy modeling technology is employed in this paper to represent the nonlinear singular systems with external noise. Considering the singular Takagi‐Sugeno fuzzy model, the passivity constraint is chosen to treat the external noises for the controlled systems. By using the parallel distributed compensation method, the fuzzy controller is designed to satisfy the Lyapunov stability conditions and passivity constraints simultaneously. These sufficient conditions can be effectively solved in terms of linear matrix inequalities, which can be solved via the convex optimization technique. At last, some numerical examples are provided to verify the applicability and effectivity of the proposed fuzzy controller design methods. [ABSTRACT FROM AUTHOR]

This paper focuses on the compressed sensing ℓ1−ℓ2$\ell _1-\ell _2$‐minimization model and develops new bounds on cumulative coherence μ1(s)$\mu _1(s)$. It is pointed out that if cumulative coherence μ1(s)$\mu _1(s)$ satisfies Equation (2) or (11), then the sparse signal can stably recover in noise model and exactly recover in free noise by ℓ1−ℓ2$\ell _1-\ell _2$‐minimization model. From this paper, it is found that based on some condition of cumulative coherence, the ℓ1−ℓ2$\ell _1-\ell _2$‐minimization model can exactly recover s‐sparse signals in noiseless cases and stably recover s‐sparse signals in the noise cases. [ABSTRACT FROM AUTHOR]

This paper presents a new time domain Zener diode compact model for transient noise simulation. SPICE2 and SPIC3 use piece‐wise linear time dependent sources for generating complex waveforms. This approach is not practical when applied to randomly generated noise. Today, through on‐going improvements to freely available circuit simulation tools, SPICE noise generation has moved to a new level. Ngspice, for example, computes white Gaussian noise 'on‐the‐fly' as transient simulation progresses. The proposed model has a simple behavioural structure that supports time domain shot, flicker, and thermal noise. The physical properties of the proposed model are introduced in the second section. This is followed by an evaluation of model performance in the third and fourth sections, including static d.c, dynamic charge, and transient noise characterisation. Finally, the fifth section summarises the conclusions of the research. [ABSTRACT FROM AUTHOR]

Summary: This paper considers the problem of convergence for the optimal linear filter with time‐correlated fading channel and channel noise (TCFCCN) proposed in Liu et al. A novel time‐varying random vector is defined where the vector includes the state error, the innovation, the fading state error and a small portion of the new measurement's noise. Based on studying the convergence of the time‐varying matrix obtained from the defined random vector, the optimal linear filter's convergence conditions are established. It is pointed out that, under proper conditions, the optimal linear filter is convergent and a set's each element converges to a unique fixed point. Two numerical examples are given to demonstrate the obtained theoretical results's effectiveness. [ABSTRACT FROM AUTHOR]

Background: Intelligibility measurement is influenced by the characteristics of a speaker, listener and contextual factors. This study addresses the clinical problem of measuring speech intelligibility in children with velopharyngeal insufficiency (VPI) in real‐world conditions. Aims: The purpose of the study was to investigate the effects of background noise on speech intelligibility in speakers with velopharyngeal insufficiency (VPI) compared to typical speech. The study further determined the contribution of nasalance and articulation accuracy in judgments of intelligibility. Methods & Procedures: Fifteen speakers diagnosed with VPI and their typical peers provided audio recordings of 20 sentences from the Hearing in Noise Test. Speech samples were presented over quiet and noise (+5 dB signal‐to‐noise ratio) conditions to 70 naïve listeners. Intelligibility scores from naïve listeners' orthographic transcriptions were obtained as the percentage of correctly identified words. Outcomes & Results: A repeated‐measures analysis of variance showed diagnosis of VPI (F(1, 28) = 13.44, p = 0.001, and presence of noise (F(1, 28) = 39.18, p < 0.001) significantly affected the intelligibility scores. There was no interaction between the diagnosis of VPI and noise (F(1, 28) = 0.06, p = 0.80). The multivariate regression analysis indicated that nasalance and articulation accuracy explain a significant amount of variance in the intelligibility scores of VPI speakers in quiet (F(2, 12) = 7.11, p < 0.05, R2 = 0.55, R2Adjusted = 0.47) and noise (F(2, 12) = 6.32, p < 0.05, R2 = 0.51, R2Adjusted = 0.43), but the significance mainly came from the effect of percentage of consonants correct (β = 0.97, t(12) = 2.90, p = 0.01). Percentage of consonants correct significantly increased the speech intelligibility in either with or without noise conditions. Conclusions & Implications: The current work suggests that background noise will significantly affect reductions in intelligibility in both groups; the effect is more prominent in VPI speech. It was also further noted that articulation accuracy significantly affected intelligibility in quiet and noise rather than nasalance scores. WHAT THIS PAPER ADDS: What is already known on the subject: Intelligibility measurement is influenced by the characteristics of a speaker, listener and contextual factors. Accordingly, it is essential to determine the degree to which speech assessments in the clinic can predict communication difficulties in the presence of background noise in real life. Background noise can adversely cause speech intelligibility degradation in individuals with speech disorders. What this study adds: The study examined the effects of background noise on speech intelligibility in speakers with velopharyngeal insufficiency (VPI) secondary to cleft palate compared to typical speech. The study results suggested that the presence of background noise will significantly affect reductions in intelligibility in both groups; however, the effect is more prominent in VPI speech. What are the clinical implications of this work?: We found out that the intelligibility of VPI speech is lower in the presence of background noise, and therefore, assessments of speech intelligibility in clinical settings should take this into account. To ensure effective communication in noisy environments, recommended strategies include selecting quiet locations, eliminating potential distractions and supplementing communication with nonverbal cues. It is important to recognize that the effectiveness of these strategies may vary depending on the individual and the specific communication context. [ABSTRACT FROM AUTHOR]

Summary: While location information sharing technology provides convenience for unmanned driving and journey navigation, user journey information sharing has also become a disaster for privacy information leakage. The traditional differential privacy method can only perturb the data entirely and cannot consider the design of data availability. In this paper, the difference privacy algorithm is improved by combining it with the Apriori algorithm, and the relevant perturbation is carried out after mining the associated data of the user's trip. In the face of possible data attacks, the privacy protection of the sensitive information of the user's actual data is ensured while the availability of the data is ensured. By testing 3000 trip data generated by experimental simulation, the results show that the correlation information between the original datasets is destroyed. However good availability is maintained after the Laplace data perturbation of the proposed algorithm for both simultaneous and multi‐person trips. [ABSTRACT FROM AUTHOR]

Motivated from the mean‐square bounded consensus (MSBD) problem of multiagent systems (MASs) with additive noise, this paper studies the joint influence of the agent dynamic structure and communication topology on the consensus. The necessary condition of MSBD is given under the output‐based consensus protocol, which is also sufficient under some mild conditions. Furthermore, the upper consensus bound is given via the solution of the Lyapunov equation. Finally, simulation results are provided to illustrate the theoretical results. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a highly stable and low‐cost 12T (HSLC12T) radiation hardened static‐random‐access‐memories (SRAM) cell is proposed in 55 nm CMOS technology. Based on polarity reversal design and read/write separation structure, the proposed HSLC12T cell can recover from any single event upsets (SEUs) induced at all its sensitive nodes and even single event double‐node‐upsets (SEDNUs) induced at its internal storage node pair Q‐QN, while also having the maximum read static noise margin (RSNM) and lower static hold power, as well as excellent write speed and write‐ability. Though the HSLC12T cell exhibits a larger read delay, it has the best overall performance of all other cells. This is proven by having the highest electrical quality metric (EQM) value, thus making the proposed HSLC12T cell a better choice for aerospace applications. [ABSTRACT FROM AUTHOR]

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This paper investigates the simultaneous state and noise covariance estimation for linear systems with inaccurate noise statistics. An enhanced adaptive Kalman filtering (EAKF) based on dynamic recursive nominal covariance estimation (DNRCE) and modified variational Bayesian (VB) inference is presented. The EAKF realizes the concurrently estimation of state and noise covariance matrices by introducing a nominal parameter in the traditional recursive covariance estimation and designing a new adaptive forgotten factor for the dynamic model of the estimated information propagation. The simulation of a target tracking example shows that, compared with the existing filters, the proposed filter has good adaptive performance for inaccurate and time‐varying noise covariance matrices. [ABSTRACT FROM AUTHOR]