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European Signal Processing Conference

作者： C. H. Taal R. C. Hendriks R. Heusdens Royal Institute of Technology (KTH) Sound and Image Processing Lab Delft University of Technology Signal and Information Processing Lab

ISBN: (纸本)9781467310680

In this paper the earlier proposed short-time objective intelligibility predictor (STOI) is simplified such that it can be expressed as a weighted l_2 norm in the auditory domain. Due to the mathematical properties of a norm, STOI can now be used with the matching pursuit algorithm in the n-of-m channel selection technique as found in several cochlear implant (CI) coding strategies. With this technique only a subset of frequency channels (electrodes) are stimulated, such that important channels can be updated more frequently and less significant channels are omitted. Intelligibility predictions with acoustic CI-simulations for normal-hearing listeners indicate that more intelligible speech is obtained with the proposed method compared to a conventional channel selection method based on peak picking. Reasons for this difference in performance are: (1) STOI considers an analysis window of a few hundreds of milliseconds in order to account for important low temporal modulations for speech intelligibility and (2) spectral leakage per channel is accounted for in the mathematical optimization process.

关键词： Speech intelligibility metric Matching pursuit Cochlear implants Channel selection intelligibility matching pursuits Matching pursuit algorithms channel selection Implants and Prostheses Speech Intelligibility Optimization Procedure MILLISECOND channels pursuit algorithms indium

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Compressive sensing signal reconstruction based on stagewise gradient pursuit

Compressive sensing signal reconstruction based on stagewise...

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International Conference on Information and Communication Technology Convergence (ICTC)

作者： Feng Lei Liu Bing Qiao JiaQing Feng Shou Automatic Test and Control Institute Harbin Institute of Technology Harbin China

This paper mainly studied the algorithm for compressive sensing signal reconstruction, aiming to reduce the time of reconstruction algorithm. By analyzing the characteristics of the commonly used of orthogonal matching pursuit, we choosed two key steps of it to improve. Using stagewise algorithm in the process of atomic selection, while using gradient pursuit algorithm in the process of projecting the allowance to the subspace, to achieve a reconstruction algorithm, which based on stagewise gradient pursuit. The simulation results show that, compared with basic algorithm based on the orthogonal matching pursuit, the proposed algorithm has obvious reduction in time of reconstruction.

关键词： Matching pursuit algorithms Signal processing algorithms Compressed sensing Reconstruction algorithms Signal reconstruction pursuit algorithms Atomic measurements

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A Novel SAR Imaging Strategy Based on Compressed Sensing

A Novel SAR Imaging Strategy Based on Compressed Sensing

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IEEE International Geoscience and Remote Sensing Symposium

作者： Wentao Lv Junfeng Wang Wenxian Yu Department of Electronic Engineering Shanghai Jiao Tong University

ISBN: (纸本)9781467311601

In this paper, we present a novel SAR (synthetic aperture radar) imaging algorithm based on compressed sensing (CS). We first obtain complex SAR images from raw SAR echoes, and then search all targets in complex-image domain by an improved MP (matching pursuit) algorithm. Unlike other CS-based imaging models, our algorithm has several advantages: 1) our algorithm is a two-dimensional (2-D) imaging system, rather than one-dimensional (1-D) imaging models introduced in most existing CS-based imaging algorithms;2) unlike low efficiencies of most reconstruction algorithms, our method has an efficient reconstruction rate;3) our imaging model applies existing SAR imaging systems, and inherits current SAR imaging results. The experimental results using real SAR echo data demonstrate the effectiveness of our algorithm.

关键词： Compressed sensing Complex-image domain Matching pursuit Point spread function estimation Radar polarimetry Compressed sensing Reconstruction algorithm Rescue Synthetic aperture radar Specific absorption rate SAFETY ANALYSIS REPORTS algorithms pursuit algorithms Imaging Echoes

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Homotopy algorithm using dichotomous coordinate descent iterations for sparse recovery

Homotopy algorithm using dichotomous coordinate descent iter...

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Asilomar Conference on Signals, Systems & Computers

作者： Yuriy Zakharov Vítor H. Nascimento Department of Electronics University of York UK Department of Electronic Systems Engineering University of São Paulo Brazil

ISBN: (纸本)9781467350501

We propose a computationally efficient technique for recovery of sparse signals, which is based on dichotomous coordinate descent iterations, homotopy, and reweighting. We derive optimal rules for adding and removing elements to/from the support, guaranteeing that the cost function is minimized. Numerical examples show that the proposed technique achieves a mean-squared error smaller than that of the YALL1 algorithm and complexity comparable to that of the matched pursuit algorithm.

关键词： using YALL1 complexity homotopy method pursuit algorithms iterative methods descent Cost functions Coordinates Complexity

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Plate impulse response spatial interpolation with sub-Nyquist sampling

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JOURNAL OF SOUND AND VIBRATION 2011年第23期330卷 5678-5689页

作者： Chardon, G. Leblanc, A. Daudet, L. ESPCI CNRS UMR 7587 Inst Langevin Ondes & Images F-75231 Paris 05 France Univ Lille Nord France F-59000 Lille France LGCgE UArtois F-62400 Bethune France Paris Diderot Univ Paris France Inst Univ France Paris France

Impulse responses of vibrating plates are classically measured on a fine spatial grid satisfying the Shannon-Nyquist spatial sampling criterion, and interpolated between measurement points. For homogeneous and isotropic plates, this study proposed a more efficient sampling and interpolation process, inspired by the recent paradigm of compressed sensing. Remarkably, this method can accommodate any star-convex shape and unspecified boundary conditions. Here, impulse responses are first decomposed as sums of damped sinusoids, using the Simultaneous Orthogonal Matching pursuit algorithm. Finally, modes are interpolated using a plane wave decomposition. As a beneficial side effect, these algorithms can also be used to obtain the dispersion curve of the plate with a limited number of measurements. Experimental results are given for three different plates of different shapes and boundary conditions, and compared to classical Shannon interpolation. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Side Effect Interpolation vibrating plate pursuit algorithms IMPULSE RESPONSE Matching pursuit algorithms Boundary conditions Isotropic

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ROBUST SPARSE IMAGE DENOISING

ROBUST SPARSE IMAGE DENOISING

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18th IEEE International Conference on Image Processing (ICIP)

作者： Obradovic, Radovan Janev, Marko Antic, Borislav Crnojevic, Vladimir Petrovic, Nemanja I. Univ Novi Sad Fac Engn Trg Dositeja Obradovica 6 Novi Sad 21000 Serbia Heidelberg Univ Interdisciplinary Ctr Sci Comp Heidelberg Germany

ISBN: (纸本)9781457713033

In this paper, we propose a novel method for denoising images corrupted by the mixture of the additive white Gaussian noise and the heavy tailed noise. The proposed method is based on robust statistical approach, i.e. application of M-estimators in the combination with l(1) sparse regularization technique. Thus, we perform the denoising by numerical solving of the convex optimization problem. Additionally, the developed method performs denoising adaptively in order to preserve the image details, by adjusting regularization coefficients according to the local variance. The proposed denoising scheme produces excellent results, both objectively (in terms of PSNR and MSSIM) and subjectively and outperforms state-of-the-art filters for denoising heavy tailed noise in images.

关键词： Image denoising estimation pursuit algorithms gradient methods

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Review on cyclic pursuit in Spacecraft Formation Flying

Review on cyclic pursuit in Spacecraft Formation Flying

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International Conference on Recent Advances in Space Technologies (RAST)

作者： Huixin Yang Tao Yang Weihua Zhang College of Aerospace and Materials Engineering National University of Defense Technology Changsha Hunan China 410073

This paper proposes a creature behaviour-based pursuit strategy named cyclic pursuit for Spacecraft Formation Flying. Cyclic pursuit Problem is one of the most popular decentralized control methods. However, the applications in space mission are limited. A comprehensive review of the current studies on the theory of pursuit has been presented, including the fundamental principles and developments of three existing algorithms as well as the solutions based on the characteristics of different kinds of pursuit algorithm. Early-stage applications of cyclic pursuit algorithm (CyPA) have been summarized, the same to its characteristics and advantages. Two applicable simulations of Nonlinear Cyclic pursuit Algorithm (NlCyPA) have been conducted. In the end, the promising future applicability has been highlighted. Besides, further applications of Cyclic pursuit in space missions have been proposed.

关键词： pursuit algorithms Space vehicles Satellites Convergence Space missions Distributed control Multiagent systems

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Hybrid greedy pursuit

Hybrid greedy pursuit

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European Signal Processing Conference (EUSIPCO)

作者： Saikat Chatterjee Dennis Sundman Mikko Vehkaperä Mikael Skoglund Communication Theory Laboratory School of Electrical Engineering KTH - Royal Institute of Technology Stockholm Sweden

For constructing the support set of a sparse vector in the standard compressive sensing framework, we develop a hybrid greedy pursuit algorithm that combines the advantages of serial and parallel atom selection strategies. In an iterative framework, the hybrid algorithm uses a joint sparsity information extracted from the independent use of serial and parallel greedy pursuit algorithms. Through experimental evaluations, the hybrid algorithm is shown to provide a significant improvement for the support set recovery performance.

关键词： Joints Vectors Matching pursuit algorithms Noise measurement Measurement uncertainty pursuit algorithms Standards

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Automated detection of sleep EEG slow waves based on matching pursuit using a restricted dictionary

Automated detection of sleep EEG slow waves based on matchin...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Antoine Picot Harry Whitmore Florian Chapotot Sleep Metabolism and Health Center University of Chicago

ISBN: (纸本)9781424441211

In this paper, an original method to detect sleep slow waves (SSW) in electroencephalogram (EEG) recordings is proposed. This method takes advantage of a Matching pursuit algorithm using a dictionary reduced to Gabor functions reproducing the main targeted waveform characteristics. By describing the EEG signals in terms of SSW properties, the corresponding algorithm is able to identify waveforms based on the largest matching coefficients. The implemented algorithm was tested on a database of whole night sleep EEG recordings collected in 9 young healthy subjects where SSW have been visually scored by an expert. Besides being fully automated and much faster than visual scoring analysis, the results obtained to the proposed method were in excellent agreement with the expert with 98% of correct detections and a 77% concordance in event time position and duration. These results were superior from those of the classical method both in terms of sensibility and precision.

关键词： eeg sleep matching pursuits SYNCHRONIZING SWITCHES waveforms Dictionaries as Topic Professional personnel Slow waves Electroencephalography pursuit algorithms Automation

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Reinforcement learning solution to economic dispatch using pursuit algorithm

Reinforcement learning solution to economic dispatch using p...

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IEEE GCC Conference & Exhibition

作者： Imthias Ahamed T Parambath E. A. Jasmin Faisal R. Pazheri Essam A. Al-Ammar Electrical Power E.E. Department College of Engineering King Saud University Riyadh Saudi Arabia Department of Electrical and Electronics Engineering College of Engineering Thrissur Kerala India

Reinforcement learning (RL) algorithms are powerful tools that can be used to solve multi stage decision making problem. In this paper, we view Economic Dispatch (ED) problem as an n stage decision making problem and propose a novel RL algorithm which uses pursuit algorithm for making decisions at each stage during the learning process. Even though many soft computing techniques like simulated annealing, genetic algorithm and evolutionary programming have been applied to ED, they require searching for the optimal solution corresponding to each demand. In RL approach, once learning phase is over, we can find optimal dispatch for any load from a lookup table. One important issue in RL algorithm is striking a balance between exploration and exploitation during the learning phase. Here we propose to use an efficient algorithm called pursuit algorithm from theory of learning automata for balancing the exploration and exploitation during the learning phase.

关键词： Learning Economics pursuit algorithms Resource management Power systems Schedules Equations

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