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International Symposium on signal processing and Its Applications (ISSPA)

作者： M. Kaveh Department of Electrical Engineering University of Minnesota Minneapolis MN USA

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Image reconstruction of compressive sensing using digital signal processing (DSP)

Image reconstruction of compressive sensing using digital si...

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IEEE International Conference on Robotics and Biomimetics

作者： Sheng Bi Ning Xi King Wai Chiu Lai Jing Xu Quanyong Huang Department of Mechanical and Biomedical Engineering City University of Hong Kong

Compressive sensing has opened up a new path to reconstruct images from a number of samples which is far smaller than the desired resolution of the images. A novel single pixel camera system has been developed based on this theory, and it can reconstruct images with a single optical sensing element. However, the development reminds challenge because the image recovery process is complex. For example, large amount of data is computed during the image recovery process and this make real-time processing of image become difficult. In order to improve the recovery speed, Orthogonal Matching Pursuit (OMP) algorithm for image recovery of compressive sensing are designed. However, the general OMP algorithm does not fit for digital signal processing (DSP) platform because it requires large memory allocation. In this paper, the modified OMP algorithm is introduced to improve calculation time with less memory requirement. The implementation of the algorithm on DSP device is presented and verified. Besides, the integration of the designed embedded hardware structure also increases the portability of the camera system.

关键词： Digital signal processing Cameras Matching pursuit algorithms Field programmable gate arrays SDRAM Algorithm design and analysis signal processing algorithms

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Comprehensive address generator for digital signal processing

Comprehensive address generator for digital Signal Processin...

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International Conference on Industrial and Information Systems, ICIIS

作者： Kini M. Ramesh David S. Sumam Department of Electronics and Communication Engineering National Institute of Technology Karnataka Surathkal INDIA

Computational efficiency of signal processing Algorithm implemented in hardware depends on efficiency of datapath, memory speed, and generation of addresses for data access. In case of signal processing applications, pattern of data access is complex in comparison with other applications. If implemented in a general purpose processor, address generation for signal processing applications will require execution of a series of instructions and use of datapath elements like adders, shifters etc. In general, considerable processor resources and time are utilized. It is desirable to execute one loop of a kernel per clock. This demands generation of typically three addresses per clock: two addresses for data sample/coefficient and one for storage of processed data. A set of dedicated, efficient Address Generator Units (AGU) will definitely enhance the performance. This paper focuses on design and implementation of Address Generators for complex addressing modes required by Multimedia signal processing algorithms. Among other addressing modes, a novel algorithm is developed for accessing data in a Bit-Reversed order for Fast Fourier Transforms (FFT), and Zig-zag order for Discrete Cosine Transforms (DCT). When mapped to hardware, this scales linearly in gate complexity with increase in the size and uses less components.

关键词： signal generators Digital signal processing signal processing algorithms Hardware Clocks Discrete cosine transforms Computational efficiency Kernel signal design Algorithm design and analysis

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Optimization and Learning With Information Streams: Time-varying algorithms and applications

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IEEE signal processing MAGAZINE 2020年第3期37卷 71-83页

作者： Dall'Anese, Emiliano Simonetto, Andrea Becker, Stephen Madden, Liam Univ Colorado Boulder Dept Elect Comp & Energy Engn Boulder CO 80309 USA Univ Minnesota Minneapolis MN 55455 USA Natl Renewable Energy Lab Golden CO 80401 USA IBM Res Ireland Optimizat & Control Grp Dublin Ireland Delft Univ Technol Delft Netherlands Catholic Univ Louvain Louvain La Neuve Belgium IBM Res Yorktown Hts NY USA Univ Colorado Boulder Appl Math Dept Boulder CO USA

There is a growing cross-disciplinary effort in the broad domain of optimization and learning with streams of data, applied to settings where traditional batch optimization techniques cannot produce solutions at time scales that match the interarrival times of the data points due to computational and/or communication bottlenecks. Special types of online algorithms can handle this situation, and this article focuses on such time-varying optimization algorithms, with emphasis on machine leaning (ML) and signal processing (SP) as well as data-driven control (DDC). Approaches for the design of time-varying or online first-order optimization methods are discussed, with emphasis on algorithms that can handle errors in the gradient, as may arise when the gradient is estimated. Insights into performance metrics and accompanying claims are provided, along with evidence of cases where algorithms that are provably convergent in batch optimization may perform poorly in an online regime. The role of distributed computation is discussed. Illustrative numerical examples for a number of applications of broad interest are provided to convey key ideas.

关键词： Optimization signal processing algorithms Measurement Prediction algorithms Electronic mail Heuristic algorithms Clustering algorithms

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A Bayesian Approach to Recurrence in Neural Networks

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2021年第8期43卷 2527-2537页

作者： Garner, Philip N. Tong, Sibo Idiap Res Inst CH-1920 Martigny Switzerland

We begin by reiterating that common neural network activation functions have simple Bayesian origins. In this spirit, we go on to show that Bayes's theorem also implies a simple recurrence relation;this leads to a Bayesian recurrent unit with a prescribed feedback formulation. We show that introduction of a context indicator leads to a variable feedback that is similar to the forget mechanism in conventional recurrent units. A similar approach leads to a probabilistic input gate. The Bayesian formulation leads naturally to the two pass algorithm of the Kalman smoother or forward-backward algorithm, meaning that inference naturally depends upon future inputs as well as past ones. Experiments on speech recognition confirm that the resulting architecture can perform as well as a bidirectional recurrent network with the same number of parameters as a unidirectional one. Further, when configured explicitly bidirectionally, the architecture can exceed the performance of a conventional bidirectional recurrence.

关键词： Logic gates Probabilistic logic Bayes methods signal processing algorithms Hidden Markov models Training Computer architecture Neural networks bayesian statistics recurrence forward-backward algorithm speech recognition bidirectional LSTM

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Multipulse Technique Exploiting the Intermodulation of Ultrasound Waves in a Nonlinear Medium

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IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL 2009年第3期56卷 520-535页

作者： Biagi, Elena Breschi, Luca Vannacci, Enrico Masotti, Leonardo Univ Florence Florence Italy

In recent years, the nonlinear properties of materials have attracted much interest in nondestructive testing and in ultrasound diagnostic applications. Acoustic nonlinear parameters represent an opportunity to improve the information that can be extracted from a medium such as structural organization and pathologic status of tissue. In this paper, a method called pulse subtraction intermodulation (PSI), based on a multipulse technique., is presented and investigated both theoretically and experimentally. This method allows separation of the intermodulation products, which arise when 2 separate frequencies are transmitted in a nonlinear medium, from fundamental and second harmonic components, making them available for improved imaging techniques or signal processing algorithms devoted to tissue characterization. The theory of intermodulation product generation was developed according the Khokhlov-Zabolotskaya-Kuznetsov (KZK) nonlinear propagation equation, which is consistent with experimental results. The description of the proposed method, characterization of the intermodulation spectral contents, and quantitative results coming from in vitro experimentation are reported and discussed in this paper.

关键词： intermodulation products signal processing algorithms second harmonic component Imaging multiple-pulse tissue characterization Nondestructive Testing Material properties Ultrasonic Waves intermodulation nonlinearity

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Convolutive Blind Source Separation for Communication signals Based on the Sliding Z-Transform

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IEEE ACCESS 2020年 8卷 41213-41219页

作者： Jia, Yinjie Xu, Pengfei Hohai Univ Coll Comp & Informat Nanjing 210098 Peoples R China Huaiyin Inst Technol Fac Elect Informat Engn Huaian 223003 Peoples R China

Convolutive blind source separation (CBSS) is one of the main branches in the field of intelligent signal processing. Inspired by the thought of sliding discrete Fourier transform (DFT), an idea of the sliding Z-transform is introduced in the present study. Based on the sliding Z-transform, a method called the sliding Z-transform for CBSS (ZCBSS) is applied to CBSS for communication signals with the same or different frequency. It is found that the deduced algorithm can accomplish the separation task without setting any preset parameter and directly recover time-domain sources from the convolutive mixtures with the help of robust instantaneous blind source separation algorithms. Simulations are carried out accordingly, and it is concluded that the proposed approach is effective in terms of both separation performance and signal de-noising.

关键词： Blind source separation Mathematical model signal processing algorithms Finite impulse response filters Discrete Fourier transforms Time-domain analysis Frequency-domain analysis Blind source separation convolutive mixture sliding Z-transform signal de-noising

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Fast Equiconcept Search on Graph Formal Context by Attribute Topology

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第2期11卷 1469-1479页

作者： Zhang, Tao Li, Shaoze Xue, Zaifa Lu, Xin Yanshan Univ Sch Informat Sci & Engn Qinhuangdao 066000 Peoples R China Key Lab Informat Transmiss & Signal Proc Hebei Pro Qinhuangdao 066000 Peoples R China

The equiconcept, as an emerging topic in formal concept analysis, provides new ideas for analyzing the behavior in social computing. However, it takes too much time for calculation because of the high complexity. In this article, a fast equiconcept search method on graph formal context by attribute topology is proposed to improve computational efficiency. First, attribute topology is optimally represented as a graph context attribute topology (GcAT) model on the graph formal context. Then, it is proved that there is a one-to-one match between the maximal complete polygon in GcAT and the equiconcept in the graph formal context. Finally, combined with the existing attribute topology formal concept searching algorithm, the fast equiconcept search is completed. The experimental results show that by the proposed method not only all equiconcepts are searched, but also the time consumption is significantly reduced compared with the other methods over seven datasets. In addition, with the size of the dataset increasing, the computational efficiency of GcAT model improves more obviously, which indicates its superiority. All of that demonstrate the proposed method has greatly improved the efficiency of equiconcept search through GcAT on graph formal context.

关键词： Topology Lattices Social networking (online) Computational modeling Formal concept analysis Visualization signal processing algorithms Equiconcept formal concept analysis fast equiconcept search graph formal context graph context attribute topology

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DOA Estimation Based on Coherent Integration-Sparse Bayesian Learning With Time-Variant Gain-Phase Errors

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IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS 2023年第6期59卷 7951-7962页

作者： Lu, Chaojie Zheng, Jibin Yang, Tianyuan Chang, Rui Liu, Hongwei Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Chinese Acad Sci Natl Key Lab Microwave Imaging Technol Aerosp Informat Res Inst Beijing 100045 Peoples R China

Direction of arrival (DOA) estimation is an important topic of array signal processing and channels without gain-phase errors or with time-invariant gain-phase errors are assumed in most of the DOA estimation algorithms. However, with the measured data of a reconnaissance receiver system, we verify that the gain-phase error between channels is time-variation. Based on this fact, a more practical signal model with time-variant gain-phase errors is constructed. To obtain accurate DOA estimation, an algorithm termed as coherent integration-sparse Bayesian learning with time-variant gain-phase errors is (CI-SBLVGPE) devised which has two superiorities, i.e., 1) the CI operation integrates the signal energy into a single snapshot, which decreases the gain-phase errors, makes the compensation possible, and guarantees a low computational complexity;2) the priori information of the gain-phase errors, source DOA, and noise is used to reduce the computational complexity and improve the robustness. With mathematical analyses, numerical simulations, and real data processing, we validate the constructed model and superiorities of the proposed method.

关键词： Direction-of-arrival estimation Estimation signal processing algorithms Bayes methods Phased arrays Data models Measurement uncertainty Coherent integration DOA estimation gain-phase errors sparse Bayesian learning

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Blind carrier phase tracking with guaranteed global convergence

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IEEE TRANSACTIONS ON signal processing 1997年第7期45卷 1889-1894页

作者： Belouchrani, A Ren, W UNIV CALIF BERKELEY DEPT ELECT ENGN & COMP SCIBERKELEYCA 94720

Conventional blind carrier recovery algorithms have been observed to show unstable behaviors for large constellation modulation schemes such as 64-QAM or 256-QAM, In this paper, we propose a new carrier tracking approach that has guaranteed global convergence, First, we show that the carrier tracking problem is equivalent to a blind source separation problem, which involves the separation of a linear unitary mixture of two independent components that are the real and imaginary parts of the emitted signal, Then, by using a blind source separation procedure, we derive a new and robust carrier tracking algorithm with guaranteed global convergence. Some numerical simulations are provided to illustrate the effectiveness of the proposed method.

关键词： Convergence signal processing algorithms Blind equalizers Adaptive equalizers Intersymbol interference Blind source separation Quadrature amplitude modulation Phase noise Algorithm design and analysis Acoustic transducers

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