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Selective feature extraction via signal decomposition

IEEE SIGNAL PROCESSING LETTERS 1997年第1期4卷 8-11页

作者： Wang, KS Lee, CH Juang, BH AT&T BELL LABS LUCENT TECHNOL MURRAY HILL NJ 07974 USA

In this article, a mathematical framework that jointly optimizes the parameters of classifier and feature extractor is presented. In this approach, feature extraction is formulated as a process of projecting the signals onto a smaller subspace in which the statistical properties of the signal can be efficiently modeled, An algorithm, called statistical matching pursuit (SMP), is proposed to learn from the training data the optimal projection dimensions and the extent of signal reduction. The algorithm is designed to achieve unconditional convergence and can be seamlessly incorporated into the expectation-maximization (EM) algorithm employed to train the classifier. Finally, we report some experimental results on speech recognition and elaborate the potential of the proposed method.

关键词： Feature extraction Signal resolution Matching pursuit algorithms Signal processing Data mining pursuit algorithms Training data Algorithm design and analysis Convergence Speech recognition

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Performance Analysis of Compressed Sensing Given Insufficient Random Measurements

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ETRI JOURNAL 2013年第2期35卷 200-206页

作者： Rateb, Ahmad M. Syed-Yusof, Sharifah Kamilah Univ Teknol Malaysia Fac Elect Engn Telecommun Res Grp Johor Baharu Malaysia

Most of the literature on compressed sensing has not paid enough attention to scenarios in which the number of acquired measurements is insufficient to satisfy minimal exact reconstruction requirements. In practice, encountering such scenarios is highly likely, either intentionally or unintentionally, that is, due to high sensing cost or to the lack of knowledge of signal properties. We analyze signal reconstruction performance in this setting. The main result is an expression of the reconstruction error as a function of the number of acquired measurements.

关键词： Compressed sensing l(1) norm minimization sparse reconstruction reconstruction error estimation pursuit algorithms sub-Nyquist sampling

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Reliable Recovery of Hierarchically Sparse Signals for Gaussian and Kronecker Product Measurements

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 4002-4016页

作者： Roth, Ingo Kliesch, Martin Flinth, Axel Wunder, Gerhard Eisert, Jens Free Univ Berlin Dahlem Ctr Complex Quantum Syst D-14195 Berlin Germany Heinrich Heine Univ Dusseldorf Inst Theoret Phys D-40225 Dusseldorf Germany Univ Gdansk Inst Theoret Phys & Astrophys PL-80309 Gdansk Poland Univ Gothenburg Inst Math Sci S-41296 Gothenburg Sweden Chalmers Univ Technol S-41296 Gothenburg Sweden Free Univ Berlin Dept Math & Comp Sci D-14195 Berlin Germany

We propose and analyze a solution to the problem of recovering a block sparse signal with sparse blocks from linear measurements. Such problems naturally emerge inter alia in the context of mobile communication, in order to meet the scalability and low complexity requirements of massive antenna systems and massive machine-type communication. We introduce a new variant of the Hard Thresholding pursuit (HTP) algorithm referred to as HiHTP. We provide both a proof of convergence and a recovery guarantee for noisy Gaussian measurements that exhibit an improved asymptotic scaling in terms of the sampling complexity in comparison with the usual HTP algorithm. Furthermore, hierarchically sparse signals and Kronecker product structured measurements naturally arise together in a variety of applications. We establish the efficient reconstruction of hierarchically sparse signals from Kronecker product measurements using the HiHTP algorithm. Additionally, we provide analytical results that connect our recovery conditions to generalized coherencemeasures. Again, our recovery results exhibit substantial improvement in the asymptotic sampling complexity scaling over the standard setting. Finally, we validate in numerical experiments that for hierarchically sparse signals, HiHTP performs significantly better compared to HTP.

关键词： Inverse problem compressed sensing sparse vectors block sparse hierarchical sparsity hard thresholding pursuit algorithms recovery guarantee Kronecker product restricted isometry property coherence channel estimation machine-type communications

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Micro- and macrostructure of sleep EEG - A universal, adoptive time-frequency parameterization

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2006年第4期25卷 26-31页

作者： Malinowska, Urszula Durka, Piotr J. Blinowska, Katarzyna J. Szelenberger, Waldemar Wakarow, Andrzej Univ Warsaw Dept Biomed Phys PL-00681 Warsaw Poland

Electroencephalogram (EEG) provides important and unique information about the sleeping brain. Polysomnography was the major method of sleep analysis and the main diagnostic tool in sleep medicine. The standard interpretation of polysomnographic recordings describes their macrostructure in terms of sleep stages, delineated according to R&K scoring criteria. Several descriptors of sleep microstructure rely on the quantification of sleep spindles and slow wave activities, detection of arousals, etc. However, these descriptors are usually assessed by means of substantially different signal processing (or visual) methods. This hinders possibilities of combining their results into a coherent description of the sleep process. This study proposes a solution to these problems in terms of a framework based upon adaptive time-frequency approximations - a recent, advanced method of signal processing. The proposed approach provides compatibility with the visual EEG analysis and standard definitions of EEG structures and describes both the macro- and microstructure of sleep EEG. Adaptive time-frequency approximations of signals calculated by means of the matching pursuit (MP) algorithm allow for the discrimination between series of unrelated structures and oscillatory activity. The detection, parametrization, and description of all these features of sleep are based upon the same unifying approach.

关键词： Sleep Electroencephalography Matching pursuit algorithms Microstructure Adaptive signal processing Biomedical signal processing Time frequency analysis Signal processing algorithms Medical diagnostic imaging pursuit algorithms

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HOW RISCY IS DSP

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IEEE MICRO 1992年第6期12卷 10-23页

作者： SMITH, MR Dept. of Electr. & Comput. Eng. Calgary Univ. Alta. Canada

DSP algorithms require specialized features in the processors used to implement them. However, actual DSP chips are a compromise between the resources desired and the silicon space available. This article examines the characteristics of benchmark DSP algorithms. By analyzing existing DSP and RISC chip performances, it proposes an ''ideal'' scalar RISC DSP chip to accommodate the algorithms.

关键词： Signal Processing Digital Signal Processing Chips Reduced Instruction Set Computing RISC DSP Chip Benchmark DSP Architecture RIS Cs DSP Performance RISC Architectures Digital Signal Processing Digital Signal Processing Chips Reduced Instruction Set Computing Finite Impulse Response Filter Silicon Timing Performance Analysis Algorithm Design And Analysis pursuit algorithms Sparks

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A unified time-frequency parametrization of EEGs

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IEEE ENGINEERING IN MEDICINE AND BIOLOGY MAGAZINE 2001年第5期20卷 47-53页

作者： Durka, PJ Blinowska, KJ Univ Warsaw Lab Med Phys PL-00681 Warsaw Poland

Seventy years since the first recording of the human electroencephalogram (EEG), visual analysis of raw EEG traces is still the major clinical tool and point of reference for other methods, in spite of its inherent limitations: low repeatability and high cost. Seven years since the introduction of the matching pursuit (MP) algorithm, the authors have collected evidence suggesting that adaptive time-frequency approximation is a good candidate for a universal high-resolution parameterization of EEG data, compatible with the visual and spectral analysis, and applicable to a large class of problems. Here, the authors briefly discuss the need for a generally applicable method for a mathematical description (parameterization) of the signal, which would be directly related to the heritage of the traditional EEG analysis. In this context the authors discuss application of the MP algorithm. They present recent advances in analysis of sleep EEGs and discuss earlier works on event-related potentials and epileptic recordings

关键词： Time frequency analysis Electroencephalography Matching pursuit algorithms Humans Costs Approximation algorithms pursuit algorithms Spectral analysis Signal analysis Sleep

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3D Data Denoising Using Combined Sparse Dictionaries

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MATHEMATICAL MODELLING OF NATURAL PHENOMENA 2013年第1期8卷 60-74页

作者： Easley, G. Labate, D. Negi, P. Syst Planning Corp Arlington VA 22201 USA Univ Houston Dept Math Houston TX 77204 USA

Directional multiscale representations such as shearlets and curvelets have gained increasing recognition in recent years as superior methods for the sparse representation of data. Thanks to their ability to sparsely encode images and other multidimensional data, transform-domain denoising algorithms based on these representations are among the best performing methods currently available. As already observed in the literature, the performance of many sparsity-based data processing methods can be further improved by using appropriate combinations of dictionaries. In this paper, we consider the problem of 3D data denoising and introduce a denoising algorithm which uses combined sparse dictionaries. Our numerical demonstrations show that the realization of the algorithm which combines 3D shearlets and local Fourier bases provides highly competitive results as compared to other 3D sparsity-based denosing algorithms based on both single and combined dictionaries.

关键词： curvelets denoising nonlinear approximations pursuit algorithms shearlets sparse approximations wavelets

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Computational geometry in navigation and path planning

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IEEE ROBOTICS & AUTOMATION MAGAZINE 2008年第2期15卷 6-7页

作者： Gavrilova, Marina Cortes, Jorge Jarvis, Raymond Department of Physics National Taiwan Normal University Taipei Taiwan R.O.C.

The six contributions to this special issue focus on computational geometry in navigation and path planning. The issue presents the applications of computational geometry in obstacle avoidance, path planning with minimum clearance, autonomous mobile robot navigation, exploration of unknown polygonal environments, and it explores the practical relevance to the geographical information systems, mobile networks, risk avoidance, security, games, and online system design.

关键词： Computational geometry Navigation Path planning Mobile robots Orbital robotics pursuit algorithms Robot sensing systems Intelligent robots Intelligent sensors Robotics and automation

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Generalized pursuit learning schemes: New families of continuous and discretized learning automata

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IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS 2002年第6期32卷 738-749页

作者： Agache, M Oommen, BJ Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada

The fastest learning automata (LA) algorithms currently available fall in the family of estimator algorithms introduced by Thathachar and Sastry [24]. The pioneering work of these authors was the pursuit algorithm, which pursues only the current estimated optimal action. If this action is not the one with the minimum penalty probability, this algorithm pursues a wrong action. In this paper, we argue that a pursuit scheme that generalizes the traditional pursuit algorithm by pursuing all the actions with higher reward estimates than the chosen action, minimizes the probability of pursuing a wrong action, and is a faster converging scheme. To attest this, we present two new generalized pursuit algorithms (GPAs) and also present a quantitative comparison of their performance against the existing pursuit algorithms. Empirically, the algorithms proposed here are among the fastest reported LA to date.

关键词： estimator algorithms learning automata (LA) pursuit algorithms

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A Novel Pure pursuit Algorithm for Autonomous Vehicles Based on Salp Swarm Algorithm and Velocity Controller

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IEEE ACCESS 2020年 8卷 166525-166540页

作者： Wang, Rui Li, Ying Fan, Jiahao Wang, Tan Chen, Xuetao Jilin Univ Coll Software Changchun 130012 Peoples R China Jilin Univ Key Lab Symbol Computat & Knowledge Engn Minist Educ Changchun 130012 Peoples R China Space Technol Jilin Co Ltd Jilin 132013 Jilin Peoples R China Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China

Pure pursuit algorithm is one of the most effective ways of path tracking in autonomous vehicles. Nevertheless, the tracking accuracy of the existing pure pursuit algorithm is limited by the look-ahead distance. In this paper, to improve the tracking accuracy of the pure pursuit algorithm, a novel pure pursuit algorithm based on the optimized look-ahead distance named OLDPPA is proposed. Four improvements are presented in OLDPPA. Firstly, to find a better look-ahead distance of pure pursuit algorithm, salp swarm algorithm (SSA) is used in pure pursuit algorithm. Secondly, Brownian motion, a random motion mechanism of particles, is introduced in SSA to enhance its exploitation and exploration capabilities. Thirdly, to accelerate the convergence speed of SSA, a weighted mechanism which uses two different weights in the search process to adjust the salps closer to the food source quickly is assigned. Based on innovations 2 and 3, adaptive Brownian motion salp swarm algorithm (ABMSSA) is proposed and applied to pure pursuit algorithm. Finally, a velocity controller which outputs the speed of the next moment according to the distance and time interval between the look-ahead point and the current vehicle position is designed in OLDPPA, to ensure that the vehicle reaches its destination at a specified time. To verify the effectiveness and efficiency of OLDPPA, OLDPPA is applied in four different paths and the corresponding results are compared with other pure pursuit algorithms that use different look-ahead distances. Experimental results show that the tracking accuracy of OLDPPA is better than other algorithms.

关键词： pursuit algorithms Convergence Tracking Autonomous vehicles Prediction algorithms Acceleration Optimization Pure pursuit algorithm autonomous vehicles salp swarm algorithm velocity controller optimized look-ahead distance

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