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Fourier and the Early Days of Sound Analysis [DSP History]

IEEE signal processing MAGAZINE 2023年第7期40卷 11-+页

作者： Flandrin, Patrick ENS Lyon Dept Phys Lyon France

Joseph Fourier's methods (and their variants) are omnipresent in audio signal processing. However, it turns out that the underlying ideas took some time to penetrate the field of sound analysis and that different paths were first followed in the period immediately following Fourier's pioneering work, with or without reference to him. This illustrates the interplay between mathematics and physics as well as the key role played by instrumentation, with notable inventions by outsiders to academia, such as Rudolph Koenig and edouard-Leon Scott de Martinville.

关键词： Heart Technological innovation Instruments Kelvin signal processing algorithms signal processing Feature extraction

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Primal-Dual Fixed Point algorithms Based on Adapted Metric for Distributed Optimization

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2023年第6期34卷 2923-2937页

作者： Li, Huaqing Zheng, Zuqing Lu, Qingguo Wang, Zheng Gao, Lan Wu, Guo-Cheng Ji, Lianghao Wang, Huiwei Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligen Chongqing 400715 Peoples R China Chongqing Univ Coll Comp Sci Chongqing 400044 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Beihang Univ Hangzhou Innovat Inst Hangzhou 310023 Peoples R China Neijiang Normal Univ Coll Math & Informat Sci Data Recovery Key Lab Sichuan Prov Neijiang 641100 Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Image Cognit Chongqing 400065 Peoples R China Chongqing Univ Posts & Telecommun Chongqing Key Lab Computat Intelligence Chongqing 400065 Peoples R China

This article considers distributed optimization by a group of agents over an undirected network. The objective is to minimize the sum of a twice differentiable convex function and two possibly nonsmooth convex functions, one of which is composed of a bounded linear operator. A novel distributed primal-dual fixed point algorithm is proposed based on an adapted metric method, which exploits the second-order information of the differentiable convex function. Furthermore, by incorporating a randomized coordinate activation mechanism, we propose a randomized asynchronous iterative distributed algorithm that allows each agent to randomly and independently decide whether to perform an update or remain unchanged at each iteration, and thus alleviates the communication cost. Moreover, the proposed algorithms adopt nonidentical stepsizes to endow each agent with more independence. Numerical simulation results substantiate the feasibility of the proposed algorithms and the correctness of the theoretical results.

关键词： Optimization Measurement Convex functions Approximation algorithms signal processing algorithms Convergence Prediction algorithms Adapted metric method completely distributed nonsmooth convex function primal-dual fixed point algorithm randomized asynchronous iterative

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Two-Dimensional Autofocus Combined With the TSA for Spotlight SAR

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IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 2023年 16卷 9990-10000页

作者： Lin, Hao Xue, Xiaoyu Li, Ning Xing, Mengdao Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China Xidian Univ Collaborat Innovat Ctr Informat Sensing & Understa Xian 710071 Peoples R China Xidian Univ Acad Adv Interdisciplinary Res Xian 710071 Peoples R China

For high-resolution spotlight synthetic aperture radar, Doppler aliasing is always introduced in the long synthetic aperture observation time. The existence of signal Doppler aliasing will greatly affect the accuracy of motion compensation. To avoid Doppler aliasing, it is an effective strategy to use the subaperture (SA) approach. However, it will introduce the long synthetic aperture time stitching problem of signal and phase error. Compared with the SA approach, the two-step approach (TSA) based on the full aperture not only eliminates the Doppler aliasing but also avoids the signal splicing problem. Therefore, a two-dimensional (2-D) frequency-domain autofocus combined with the TSA is adopted in this article. First, TSA is used to perform dealiasing and coarse focusing imaging on full-aperture (FA) data. Second, the phase error history and the phase error form in the TSA process are analyzed and deduced, and an accurate prior structure of the phase errors is established. Then, the accurate inversion of the common 2-D phase errors is realized based on this prior structure. Finally, the autofocus process of the FA signal combined with the TSA is realized in the nonaliasing 2-D frequency domain. The validity of the recommended algorithm is verified by simulation and experimental results.

关键词： Doppler effect Azimuth Imaging Time-domain analysis Apertures signal processing algorithms Radar imaging 2-D autofocus process motion compensation (MoCo) synthetic aperture radar (SAR) two-step approach (TSA)

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Single-Cycle Independent Component Analysis Processor for In-Band Full Duplex Systems

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2025年

作者： Weng, Hao-Lun Shen, Chung-An Fouda, Mohammed E. Eltawil, Ahmed M. Natl Taiwan Univ Sci & Technol Dept Elect & Comp Engn Taipei 106335 Taiwan Rain Neuromorph Inc San Francisco CA 94110 USA King Abdullah Univ Sci & Technol Elect & Comp Engn Program Thuwal 23955 Saudi Arabia

This paper presents a single-cycle independent component analysis (ICA) algorithm and architecture for self-interference cancellation (SIC) in In-band Full-duplex (IBFD) communication systems. The proposed algorithm, AICA-EBM, incorporates the adaptive momentum (ADAM) approach with the entropy-bound estimation (EBM) to achieve rapid convergence. The simulation results show that the proposed AICA-EBM algorithm leads to a constant single-cycle processing time to achieve satisfactory SIC optimality in IBFD systems. The architecture of the ICA processor based on the proposed AICA-EBM algorithm is designed. Novel circuit structures are proposed to reduce the complexity of the ICA processor. The AICA-EBM processor is implemented by following an application-specific integrated circuit (ASIC) flow with the TSMC 90 nm process. The post-layout estimations show that Compared to previous ICA processors, the proposed design achieves a 2x improvement in processing throughput and leads to the best hardware efficiency.

关键词： signal processing algorithms Interference cancellation Convergence Throughput Wireless communication Hardware Estimation Circuits Independent component analysis Full-duplex system In-band full-duplex (IBFD) interference cancellation independent component analysis (ICA) single-cycle architecture algorithm

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Uplink signal Detection via Look-Up Table-Based AMP for Massive MIMO Systems

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IEEE ACCESS 2023年 11卷 13044-13057页

作者： Shimamura, Atsunori Takahashi, Takumi Ibi, Shinsuke Sampei, Seiichi Osaka Univ Grad Sch Engn Suita 5650871 Japan Doshisha Univ Fac Sci & Engn Kyotanabe 6100394 Japan

We propose a novel look-up table (LUT)-based multi-user detection (MUD) algorithm to imitate approximate message passing (AMP) for uplink signal detection in massive multi-user multi-input multi-output (MU-MIMO) systems. When AMP is implemented with double-precision arithmetic, the dramatic increase in power consumption and process latency becomes a major barrier to practical application, as the system scale expands. To circumvent this issue, we design a novel referential AMP detector composed of many small LUTs cascaded hierarchically, where only informative integer-valued messages are exchanged on a factor graph (FG). Our method tracks the discrete distribution of the LUT outputs according to the multi-layer structure, and successively determines non-uniform quantization thresholds of the LUTs, using an unsupervised learning approach. Specifically, the thresholds at each level of the hierarchy, i.e., layer, are optimized by clustering with the Lloyd-Max algorithm with initial values given by the k-means++ method, in order to minimize the performance degradation caused by quantization errors. The efficacy of the proposed referential AMP detector is confirmed by numerical simulations, which show that the proposed method significantly outperforms the state-of-the-art (SotA) in terms of the bit error rate (BER) performance in various channel models. The results also indicate the referential AMP is robust to changes in wireless channels, and then clarify the reason in terms of the algorithmic structure.

关键词： Table lookup Multiuser detection Wireless communication Quantization (signal) Detectors Uplink signal processing algorithms Massive MIMO detection approximate message passing quantization look-up table unsupervised learning

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Deep Optical Coding Design in Computational Imaging: A data-driven framework

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IEEE signal processing MAGAZINE 2023年第2期40卷 75-88页

作者： Arguello, Henry Bacca, Jorge Kariyawasam, Hasindu Vargas, Edwin Marquez, Miguel Hettiarachchi, Ramith Garcia, Hans Herath, Kithmini Haputhanthri, Udith Ahluwalia, Balpreet Singh So, Peter Wadduwage, Dushan N. Edussooriya, Chamira U. S. Univ Ind Santander Syst Engn Dept Bucaramanga 680002 Colombia UIS Bucaramanga 680002 Colombia Harvard Univ Ctr Adv Imaging Cambridge MA 02138 USA Univ Ind Santander Bucaramanga 680002 Colombia Harvard Univ Div Sci Fac Arts & Sci Cambridge MA 02138 USA UiT Arctic Univ Norway Dept Phys & Technol Tromso Norway MIT Dept Mech & Biol Engn Cambridge MA 02139 USA Harvard Univ Ctr Adv Imaging Wadduwage Lab Cambridge MA 02138 USA Univ Moratuwa Dept Elect & Telecommun Engn Moratuwa Sri Lanka

Computational optical imaging (COI) systems leverage optical coding elements (CEs) in their setups to encode a high-dimensional scene in a single or in multiple snapshots and decode it by using computational algorithms. The performance of COI systems highly depends on the design of its main components: the CE pattern and the computational method used to perform a given task. Conventional approaches rely on random patterns or analytical designs to set distribution of the CE. However, the available data and algorithm capabilities of deep neural networks (DNNs) have opened a new horizon in CE data-driven designs that jointly consider the optical and computational decoders. Specifically, by modeling the COI measurements through a fully differentiable image-formation model that considers the physics-based propagation of light and its interaction with the CEs, the parameters that define the CE and the computational decoder can be optimized in an end-to-end (E2E) manner. Moreover, by optimizing just CEs in the same framework, inference tasks can be performed from pure optics. This work surveys the recent advances in CE data-driven design and provides guidelines on how to parameterize different optical elements to include them in the E2E framework. As the E2E framework can handle different inference applications by changing the loss function and the DNN, we present low-level tasks such as spectral imaging reconstruction or high-level tasks such as pose estimation with privacy preservation enhanced by using optimal task-based optical architectures. Finally, we illustrate classification and 3D object-recognition applications performed at the speed of the light using all-optics DNNs.

关键词： Privacy Three-dimensional displays Optical design Computational modeling signal processing algorithms Optical imaging Encoding

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Research on Mixed-Strategy Based Grey Wolf Optimization for Gene Expression Classification

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IEEE ACCESS 2023年 11卷 103254-103273页

作者： Wang, Yang Liaoning Petrochem Univ Coll Sci Fushun 113001 Peoples R China

With the advantages of easy implement and few adjustment parameters, grey wolf optimization (GWO) performs well in solving global optimization problems. However, the original GWO can suffer from slow convergence speed and plunge into local optimums in dealing with complex problems. To address these issues, improvement of mixed-strategy based grey wolf optimization (MGWO) is proposed in this paper. Firstly, we present chaos strategy in combination with quasi-opposition learning strategy for generating more high-quality population to improve convergence speed of the algorithm. Then, we embed sine cosine mechanism into the original GWO to jump out of local optimums. We utilize the interaction of sine and cosine to better balance the exploration and exploitation capabilities of the algorithm. Finally, we use benchmark functions for testing the performance of proposed algorithm. Experimental results demonstrate that proposed algorithm can improve search accuracy and convergence speed compared with other state-of-the-art algorithms. Simultaneously, to verify further the performance of proposed algorithm, classification problems on gene expression datasets are also evaluated. Both continuous and binary versions of MGWO are respectively used for completing parameters optimization and feature selection. Experimental results show that proposed algorithm has better performance than others in terms of Sensitivity, Specificity, G-mean, Accuracy and F-measure.

关键词： Optimization Classification algorithms Behavioral sciences Heuristic algorithms Statistics Sociology signal processing algorithms Grey wolf optimization chaos strategy quasi-opposition learning sine cosine mechanism gene expression dataset

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Contextual Bandit-Based Amplifier IBO Optimization in Massive MIMO Network

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IEEE ACCESS 2023年 11卷 127035-127042页

作者： Hoffmann, Marcin Kryszkiewicz, Pawel Poznan Univ Tech Inst Radiocommun PL-60965 Poznan Poland

Massive Multiple-Input Multiple-Output (MMIMO) is one of the 5G key enablers. Though, most of the works consider MMIMO under assumptions of ideal hardware. It has been shown that Power Amplifiers (PAs) introduce nonlinear distortion while operating close to their saturation power. Moreover, these distortions are in some cases beamformed toward the user, preventing antenna array gain from solving this problem. One of the possible solutions is an adaptive adjustment of the PA operating point, measured by Input Back off (IBO), to find a balance between wanted signal power and nonlinear distortion power. This work proposes a Contextual Bandit-Based IBO Optimization (COBBIO) algorithm to find rate-maximizing IBO for a given user's radio conditions using learning through interaction. The proposed solution is tested in a realistic analog beamforming MMIMO cell simulator with multiple functional blocks, e.g., precoder, user scheduler, and utilizing an accurate 3D Ray-Tracing radio channel model. COBBIO provides throughput gains both over fixed-IBO schemes and state-of-the-art analytical IBO adjustment algorithms. The highest gains were observed for the so-called cell-edge users, where up to 83% improvement over the state-of-the-art algorithm was observed for the proposed COBBIO algorithm.

关键词： OFDM signal to noise ratio Throughput Nonlinear distortion Optimization 5G mobile communication signal processing algorithms Machine learning Massive MIMO 5G machine learning nonlinear distortion input back-off (IBO)

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Frequency Estimation in Data Streams: Learning the Optimal Hashing Scheme

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2023年第2期35卷 1541-1553页

作者： Bertsimas, Dimitris Digalakis, Vassilis MIT Sloan Sch Management Cambridge MA 02139 USA MIT Operat Res Ctr Cambridge MA 02139 USA

We present a novel approach for the problem of frequency estimation in data streams that is based on optimization and machine learning. Contrary to state-of-the-art streaming frequency estimation algorithms, which heavily rely on random hashing to maintain the frequency distribution of the data steam using limited storage, the proposed approach exploits an observed stream prefix to near-optimally hash elements and compress the target frequency distribution. We develop an exact mixed-integer linear optimization formulation, which enables us to compute optimal or near-optimal hashing schemes for elements seen in the observed stream prefix;then, we use machine learning to hash unseen elements. Further, we develop an efficient block coordinate descent algorithm, which, as we empirically show, produces high quality solutions, and, in a special case, we are able to solve the proposed formulation exactly in linear time using dynamic programming. We empirically evaluate the proposed approach both on synthetic datasets and on real-world search query data. We show that the proposed approach outperforms existing approaches by one to two orders of magnitude in terms of its average (per element) estimation error and by 45-90 percent in terms of its expected magnitude of estimation error.

关键词： Frequency estimation Machine learning algorithms Machine learning signal processing algorithms Optimization Task analysis Monitoring Data streams streaming frequency estimation learning to hash optimal hashing scheme

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Fading Noise Suppression Method of Φ-OTDR System Based on GA-VMD Algorithm

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IEEE SENSORS JOURNAL 2023年第19期23卷 22608-22619页

作者： Li, Tian-Xiong Zhang, Fu-Dong Lin, Jun Bai, Xing-Ye Liu, Hao-Zhuang Jilin Univ Coll Instrumentat & Elect Engn Changchun 130061 Peoples R China

A distributed optical fiber acoustic sensing system (DAS) based on phase-sensitive optical time domain reflectometry (Phi-OTDR) can detect the vibration information along an optical fiber and has been widely used for various engineering detections;however, the high-coherence detection light source used in a DAS will cause coherent fading in the fiber, leading to system fading noise and affecting the monitoring of the target vibration events. In order to solve the problem of the fading noise in the DAS, this study considered a method of suppressing the fading noise based on the genetic algorithm (GA) and variational mode decomposition (VMD). Furthermore, the parameter selection problem in the VMD method is improved by introducing the GA. By introducing sample entropy as a fitness function and combining it with the GA, this method adaptively searches for the optimal decomposition parameters by iterating the minimum value of the fitness function according to the type of input signal. Then, it decomposes the noisy DAS data into multiple intrinsic mode functions (IMFs), and the permutation entropy and time-frequency domain information of each component were used to extract the effective IMF components for signal reconstruction to obtain the denoised signal. Experimental results show that compared with empirical mode decomposition (EMD), ensemble EMD (EEMD), and complete EEMD (CEEMD) methods, the proposed method can eliminate the mode aliasing problem, effectively suppress the fading noise of the DAS, improve the signal-to-noise ratio, and reduce the root-mean-square error. It is, thus, possible to more accurately monitor vibration events, improving the practical application value of the DAS.

关键词： signal processing algorithms Fading channels Optical fibers Optical fiber sensors Genetic algorithms Feature extraction signal resolution Distributed optical fiber fading noise parameter optimization variational mode decomposition (VMD)

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