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Phase Retrieval Using Deep Dual Alternating Direction Method of Multipliers Network With Deep Sparse Prior Knowledge

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IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE processing 2025年 33卷 557-569页

作者： Kim, Moogyeong Chung, Wonzoo Korea Univ Dept Artificial Intelligence Seoul 02841 South Korea

In this paper, a deep phase retrieval algorithm for speech signals based on the dual Alternating Direction Method of Multipliers (ADMM) incorporating a deep prior network that exploits the sparsity of speech signals is presented. The proposed network, named DADMM-net, unfolds the dual ADMM for the $\ell _{1}$-regularized non-convex optimization problem of phase retrieval with several two-dimensional convolutional neural networks (2D-CNNs). In order to efficiently optimize the deep unfolding network for high-dimensional parameter vectors, a novel updating scheme referred to as soft coordinate descent (soft-CD) is proposed, where dual parameter updates are determined through interpolation between the current values and the updated values coordinate-wise with respect to the weights computed by deep networks in each layer. Numerical simulations on a publicly available dataset confirm the state-of-the-art performance of the proposed method in terms of perceptual evaluation of speech quality and short-time objective intelligibility with a significantly faster convergence speed compared to existing methods.

关键词： Optimization Convex functions Time-domain analysis Spectrogram signal processing algorithms Vectors Sparse approximation Approximation algorithms Knowledge engineering Time-frequency analysis Deep sparse prior deep unfolding dual ADMM non-convex optimization phase retrieval

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A Feedback Correction De-Noising Algorithm Based on the Wavelet Coefficients

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Chinese Journal of Electronics 2025年第3期23卷 516-520页

作者： Ning Li Zhen Cao Zhongliang Deng School of Electronic Engineering Beijing University of Posts and Telecommunications Beijing China

The localization of satellite interference sources under the condition of low SNR has been a hot research topic at current, where the signal de-noising is important in the following positioning work. With the help of the wavelet analysis theory, this paper proposes a de-noising algorithm based on the wavelet coefficients in low SNR. After correcting and reconstructing the signal by the correction coefficients, we could obtain the SNR and Root mean square error (RMSE), and then we could correct the signal for the second time. The simulation results show that this de-noising algorithm can effectively remove the noise of the signal in low SNR, which would have a good effect on the estimation of time delay parameter in the localization of satellite interference sources.

关键词： Location awareness Satellites Delay effects Simulation Noise reduction signal processing algorithms Interference Wavelet analysis signal to noise ratio Wavelet coefficients

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引用

IEEE TRANSACTIONS ON signal processing 1996年第4期44卷 827-833页

作者： Moon, TK Electrical and Computer Engineering Department Utah State University Logan UT USA

A signal may contain information that is preserved by certain transformations of the signal, For example, the information phase-modulated signal is not altered by amplitude scaling of the signal. Many processing techniques have been developed to exploit such similarities. In the past, these algorithms have been developed in isolation without regard to common principles of invariance that tie them together, In this paper, similarity methods are presented as a unified method of designing processing algorithms invariant to specified transformations, These methods are based upon groups of continuous transformations known as local Lie groups and lead to a quasilinear partial differential equation. Solution of this partial differential equation specifies the form the signal processing operations must take. This form can then be applied using engineering judgment for algorithmic implementation, The paper presents an extended tutorial on Lie groups and similarity methods and quasilinear differential equations drawn from the mathematical literature, This is followed by several examples of signal processing interest that demonstrate that the similarity techniques may be applicable in certain kinds of signal processing problems.

关键词： signal processing signal processing algorithms Partial differential equations Algorithm design and analysis Differential equations Mathematics Integral equations Moon Design methodology Phase modulation

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MATLAB for signal processing on Multiprocessors and Multicores

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IEEE signal processing MAGAZINE 2010年第2期27卷 40-49页

作者： Samsi, Siddharth Gadepally, Vijay Krishnamurthy, Ashok Ohio State Univ Dept Elect & Comp Engn Columbus OH 43210 USA

MATLABR is a popular choice for algorithm development in signal and image processing. While traditionally this is done using sequential MATLAB running on desktop systems, recent years have seen a surge of interest in running MATLAB in parallel to take advantage of multi-processor and multi-core systems. In this paper, we discuss three variations of multi-processor parallel MATLAB, two of which are available as commercial, supported products. We also consider running MATLAB with key computations speeded up using multi-threaded computations on multi-core GPGPUs. Two signal processing kernels (FFT and convolution) and two full applications (SAR imaging and Superconducting Quantum Interference Devices) are used to illustrate the use of parallel MATLAB.

关键词： MATLAB signal processing Multicore processing signal processing algorithms Image processing Surges Radar signal processing Kernel Fast Fourier transforms Convolution

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A signal-processing IMPLEMENTATION FOR AN IBM-PC-BASED WORKSTATION

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IEEE MICRO 1985年第5期5卷 52-67页

作者： RIEDEL, NK MCANINCH, DA FISHER, C GOLDSTEIN, NB HARVEY MUDD COLL ENGN CLIN OFFCLAREMONTCA 91711 MA COM LINKABIT INC SAN DIEGOCA

This TMS32010-based, single-board system calculates fast Fourier transforms. Special software makes based calculations transparent to the Fortran user.

关键词： signal processing Workstations signal processing algorithms Frequency Fast Fourier transforms Discrete Fourier transforms Hardware Circuit testing Educational institutions Design for testability

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Reproducible Research in signal processing

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IEEE signal processing MAGAZINE 2009年第3期26卷 37-47页

作者： Vandewalle, Patrick Kovacevic, Jelena Vetterli, Martin Carnegie Mellon Univ Ctr Bioimage Informat Pittsburgh PA 15213 USA Columbia Univ New York NY USA Univ Calif Berkeley Berkeley CA 94720 USA Ecole Polytech Fed Lausanne Commun Syst Dept Lausanne Switzerland

What should we do to raise the quality of signal processing publications to an even higher level? We believe it to be crucial to maintain the precision in describing our work in publications, ensured through a high-quality reviewing process. We also believe that if the experiments are performed on a large data set, the algorithm is compared to the state-of-the-art methods, the code and/or data are well documented and available online, we will all benefit and make it easier to build upon each other's work. It is a clear win-win situation for our community: we will have access to more and more algorithms and can spend time inventing new things rather than recreating existing ones.

关键词： signal processing signal processing algorithms Scholarships Digital signal processing Wikipedia Testing Advertising Programming Education Reproducibility of results

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APPLICATION OF FAST SUBSPACE DECOMPOSITION TO signal-processing AND COMMUNICATION PROBLEMS

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IEEE TRANSACTIONS ON signal processing 1994年第6期42卷 1453-1461页

作者： XU, GG CHO, YM KAILATH, T STANFORD UNIV INFORMAT SYST LABSTANFORDCA 94305

In [1], we described a class of fast subspace decomposition (FSD) algorithms. Though these algorithms can be applied to solve a variety of signal processing and communication problems with significant computational reduction, we shall focus our discussion on two typical applications. i.e., sensor array processing and time series analysis. In many cases, replacing usual eigenvalue decomposition (EVD) or singular value decomposition (SVD) by FSD is quite straightforward. However, the FSD approach can exploit more structure of some special problems to further simplify the implementation. In this paper, we shall first discuss the implementation details of FSD such as how to choose an optimal starting vector, how to handle correlated noise, and how to exploit additional matrix structure for further computational reduction. Then, we describe an FSD approach targeted at data matrices (rectangular N x M, N greater-than-or-equal-to M), which requires only O(NMd) flops where d denotes the signal subspace dimension versus a regular O(N M2 + M3) SVD. The computational reduction is substantial in tropical scenarios d much less than M less-than-or-equal-to N. In the spectrum estimation problems, the data matrix has additional structure such as Toeplitz or Hankel, we shall finally show how FSD can exploit such structure for further computational reduction.

关键词： signal processing signal processing algorithms Array signal processing Sensor arrays signal analysis Time series analysis Algorithm design and analysis Eigenvalues and eigenfunctions Singular value decomposition Noise reduction

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A DIGITAL signal-processing ALGORITHM FOR DETECTING ARCING FAULTS ON POWER DISTRIBUTION FEEDERS

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IEEE TRANSACTIONS ON POWER DELIVERY 1989年第1期4卷 132-140页

作者： RUSSELL, BD CHINCHALI, RP Texas A and M University College Station TX USA

signal processing hardware and software that can be used to improve the detection of certain power system faults using computer relays are discussed. Integrated systems and architectures for monitoring several fault-sensitive parameters have been investigated. A suggested architecture utilizing several processors is presented. Several fault-sensitive parameters for the detection of arcing faults are presented. A detection methodology based on these parameters is described, and a partial solution to the problem of directionality is discussed. The use of a knowledge-based environment to modify protection criteria is suggested.< >

关键词： Digital signal processing signal processing algorithms Fault detection Electrical fault detection Computer architecture Hardware Power system faults Digital relays Power system relaying Computerized monitoring

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Two-dimensional signal processing techniques for airborne laser bathymetry

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 1996年第1期34卷 57-66页

作者： Wong, HC Antoniou, A Department of Electrical and Computer Engineering University of Victoria Victoria BC Canada

The application of two-dimensional (2-D) signal processing to data collected in airborne laser bathymetry is investigated. Specifically, a type of 2-D filter for the suppression of impulsive noise in irregularly-spaced data based on order-statistics filtering is developed. An algorithm which incorporates this type of filter along with a sophisticated 2-D interpolation technique is constructed to automate the filtering process. An adaptive 2-D filtering technique that can be applied to raw bathymetric profiles to remove wideband noise is then discussed. The results obtained show that each type of filtering enhances the accuracy of bathymetric measurement quite significantly.

关键词： signal processing Oceanographic techniques Sea measurements Geologic measurements Laser noise Filtering Oceans Acoustic noise signal processing algorithms Filters

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Statistical reference criteria for adaptive signal processing in digital communications

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IEEE TRANSACTIONS ON signal processing 1997年第1期45卷 14-31页

作者： SalaAlvarez, J VazquezGrau, G Department of Signal Theory and Communications Campus Nord UPC Mòdul D5 Universitat Poliltècnica de Catalunya Barcelona Spain

A general criterion for the design of adaptive systems in digital communications called the statistical reference criterion is proposed. The criterion is based on imposition of the probability density function of the signal of interest at the output of the adaptive system, with its application to the scenario of highly powerful interferers being the main focus of this paper, The knowledge of the pdf of the wanted signal is used as a discriminator between signals so that interferers with differing distributions are rejected by the algorithm, Its performance is studied over a range of scenarios, Equations for gradient-based coefficient updates are derived, and the relationship with other existing algorithms like the minimum variance and the Wiener criterion are examined.

关键词： Adaptive signal processing Digital communication Cost function signal processing algorithms Adaptive systems Density functional theory signal processing Robustness Convergence Digital signal processing

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