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International Conference on Mechatronics and Control (ICMC)

作者： Jing Wang Jisheng Zhang Chang Chen Feng Tian Lingli Cui National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing China Beijing Aerospace Automatic Control Institute Beijing China Key Laboratory of Advanced Manufacturing Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781479925391

The sparse decomposition based on basic pursuit is an adaptive sparse expression of the signals. An adaptive basic pursuit algorithm that uses an impulse dictionary is introduced in this article for rolling bearing vibration signal processing and fault diagnosis. In the first, a new dictionary model is constructed according to the characteristics and mechanism of rolling bearing faults. Rotational speed of bearing, dimensions of bearing and bearing fault situation, among other parameters incorporates the new mode which could simulate the real fault impulse in different fault levels. Secondly a new method of dictionary establishment called adaptive impulse dictionary combine with basic pursuit introduced in this paper for bearing fault diagnosis. Adaptive impulse dictionary is created by changing characteristic parameters progressively, which make the dictionary built by this method has a lower redundancy and a higher relevance between each dictionary atom and the analyzed vibration signal. The basic pursuit algorithm of an adaptive impulse dictionary is adopted to analyze experiment signal of the early-stage fault signals and composite fault signals of the bearing. The results demonstrate the effectiveness of the basic pursuit algorithm that uses the adaptive impulse dictionary.

关键词： Dictionaries pursuit algorithms Fault diagnosis Vibrations Adaptation models Time-frequency analysis

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Compressed Sensing Data Reconstruction Using a Modified Subspace pursuit Algorithm Under the Condition of Unknown Sparsity

Compressed Sensing Data Reconstruction Using a Modified Subs...

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International Congress on Image and Signal Processing

作者： Xingyuan Wang Lin Ni Dept. of Electron. Eng. & Inf. Sci. (EEIS) Univ. of Sci. & Technol. of China Hefei China

ISBN: (纸本)9781479958368

This paper introduces the fundamental knowledge of compressed sensing theory, and analyzes the important reconstruction algorithms such as orthogonal matching pursuit, subspace pursuit, but we should know the sparse degree. The sparsity adaptive matching pursuit algorithm can be terminated by setting the conditions to make adaptive sparse degree. This paper puts forward a modified sparsity adaptive algorithm based on those three algorithms. The simulation results show that new algorithm can accurately reconstruct the original signal, and has better results than SAMP.

关键词： compressed sensing iterative methods signal reconstruction time-frequency analysis SAMP adaptive sparse degree compressed sensing data reconstruction algorithm modified subspace pursuit algorithm orthogonal matching pursuit sparsity adaptive matching pursuit algorithm unknown sparsity condition Algorithm design and analysis Approximation algorithms Compressed sensing Image reconstruction Matching pursuit algorithms Reconstruction algorithms Signal processing algorithms sparse approximation sparsity adaptive matching pursuit subspace pursuit Compressed sensing Signal reconstruction Matching pursuit algorithms 4-(4-sulfophenylazo)-2-mercuriphenol Reconstruction algorithm Algorithm design and analysis matching pursuits Signal processing algorithms Time frequency analysis Approximation algorithms image reconstruction iterative methods data reconstruction pursuit algorithms

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An Adaptive Matching pursuit Algorithm for Linear Frequency Modulation Signal Compressive Sampling

An Adaptive Matching Pursuit Algorithm for Linear Frequency ...

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International Congress on Image and Signal Processing

作者： Qi Yu Jubo Zhu Coll. of Sci. Nat. Univ. of Defense Technol. Changsha China

ISBN: (纸本)9781479958368

We focus on the problem of compressive sampling of Linear Frequency Modulation (LFM) signal via Matching pursuit. We designed an adaptive matching pursuit algorithm through dynamic dictionary optimization. Results from the sparse property of LFM under Chirplet Basis, we use Chirplet atom to generate dictionary. Then by feeding the information of signal back into dictionary generating process, the grid error can be reduced significantly. It also allows us to get better parameter estimation results and lower signal sampling rate. We demonstrate computing performance on a LFM signal sampling example.

关键词： chirp modulation compressed sensing frequency modulation iterative methods linear programming parameter estimation radar signal processing signal sampling time-frequency analysis CS radar signal processing Chirplet atom Chirplet basis LFM signal compressive sampling LFM sparse property adaptive matching pursuit algorithm dynamic dictionary optimization grid error reduction linear frequency modulation signal lower signal sampling rate signal information feeding Accuracy Algorithm design and analysis Chirp Dictionaries Heuristic algorithms Matching pursuit algorithms Signal processing algorithms Chirp modulation Matching pursuit algorithms Parameter estimation Dictionaries as Topic signal sampling Algorithm design and analysis Radar signal processing Signal processing algorithms Heuristic algorithms Frequency modulation Compressed sensing Time frequency analysis iterative methods linear programming pursuit algorithms

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Adaptive Digital Beamforming Algorithm Using Neighborhood Filter

Adaptive Digital Beamforming Algorithm Using Neighborhood Fi...

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Asia-Pacific Microwave Conference

作者： Di Zhu Chen Miao Jingping Yang Yuan Qiu Bo Li School of Electronic Engineering and Optoelectronic Technology Nanjing University of Science and Technology Key Lab of Radio Astronomy Purple Mountain Observatory CAS School of Electronic Science and Engineering Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781479987689

Based on Neighborhood filter, this paper provided a novel subspace pursuit algorithm of compressive sensing for beamforming. After choose the best atom of the dictionary in matching pursuit, Neighborhood filter would find atoms which have a strong relativity larger than a set value. The results obtained this method can avoid overmatching, and get a balance between calculate quantity and the rate of convergence. It has a better performance than conditional LCMV in the condition of large SNR.

关键词： Beamforming Neighborhood Compressed sensing Filters Dictionaries as Topic Atoms pursuit algorithms Converge set value

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Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2014年第12期20卷 2417-2426页

作者： Sicat, Ronell Krueger, Jens Moeller, Torsten Hadwiger, Markus KAUST Thuwal Saudi Arabia Univ Duisburg Essen Essen Germany Univ Vienna A-1010 Vienna Austria

This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.

关键词： Multi-resolution representations sparse approximation pursuit algorithms large-scale volume rendering

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The cosparse analysis model and algorithms

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APPLIED AND COMPUTATIONAL HARMONIC ANALYSIS 2013年第1期34卷 30-56页

作者： Nam, S. Davies, M. E. Elad, M. Gribonval, R. Ctr Rech INRIA Rennes Bretagne Atlantique F-35042 Rennes France Univ Edinburgh Sch Engn & Elect Edinburgh EH9 3JL Midlothian Scotland Technion Israel Inst Technol Dept Comp Sci IL-32000 Haifa Israel

After a decade of extensive study of the sparse representation synthesis model, we can safely say that this is a mature and stable field, with clear theoretical foundations, and appealing applications. Alongside this approach, there is an analysis counterpart model, which, despite its similarity to the synthesis alternative, is markedly different. Surprisingly, the analysis model did not get a similar attention, and its understanding today is shallow and partial. In this paper we take a closer look at the analysis approach, better define it as a generative model for signals, and contrast it with the synthesis one. This work proposes effective pursuit methods that aim to solve inverse problems regularized with the analysis-model prior, accompanied by a preliminary theoretical study of their performance. We demonstrate the effectiveness of the analysis model in several experiments, and provide a detailed study of the model associated with the 2D finite difference analysis operator, a close cousin of the TV norm. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Synthesis Analysis Sparse representations Union of subspaces pursuit algorithms Greedy algorithms Compressed-sensing

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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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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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Joint Channel Estimation and Pre-Equalization for Monobit Transmission System

Joint Channel Estimation and Pre-Equalization for Monobit Tr...

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2nd IEEE/CIC International Conference on Communications in China (ICCC)

作者： Li, Pengfei Wang, Zhiyong Yin, Huarui Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Peoples R China

ISBN: (纸本)9781467328159

High date rate is one of the important targets in future communication systems, which requires large bandwidth. However, the multibit analog-to-digital converter (ADC) with such a high rate and large bandwidth will have a large power consumption and high implementation complexity. Therefore, monobit receivers have been proposed. In this paper, we concentrate on the channel estimation and equalization for monobit transmission system, which is not investigated up to now. To our surprise, the channel state information (CSI) can be estimated accurately in the condition of one bit quantization, with the proposed greedy pursuit algorithm and iterative method. The minimum mean square error (MMSE) pre-equalizer is then applied to suppress the effect of inter symbol interference (ISI) of the multipath channel. The bit error rate (BER) performance of the proposed algorithm is presented and compared with that of full CSI acknowledge. With the pre-equalizer, the ISI effect is canceled almost completely and "error floor" is eliminated as well. The BER performance can be boosted significantly.

关键词： channel estimation bit error rate performance COMMUNICATION SYSTEMS pre-equalization Transmission systems pre-equalizer Power consumption Equalization Mean square error analog digital converter pursuit algorithms

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Application of pursuit algorithms for space missions

Application of Pursuit Algorithms for space missions

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IEEE Conference on Aerospace

作者： Tao Yang Gianmarco Radice Weihua Zhang Xiaoqian Chen Zhongwei Wang Department of Astronautics and Material Engineering National University of Defense Technology Changsha Hunan China Department of AeroSpace Engineering University of Glasgow Glasgow UK

This paper investigates the applicability of pursuit Algorithm (PA), including Classic pursuit Algorithm in Circle (ClaPAIC) and Cyclic pursuit Algorithm (CyPA) into the field of space missions. The implementation of PA has been applied to a number of typical scenarios: formation replenishment, rendezvous and docking and formation reconfiguration. Simulation results show the effectiveness when ClaPAIC and CyPA are accurately designed for the mission, and indicate that PA may be a promising tool in the design of spacecraft maneuvers. The small fuel cost in the case of TPF deployment and formation maintenance shows that PA control is also effective when ClaPAIC and CyPA are arranged, and control gain k alpha is selected properly.

关键词： pursuit algorithms Space missions Space vehicles Space technology Control systems Paper technology Aerospace materials Costs Runtime Propulsion

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