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检索条件"主题词=Pursuit Algorithms"

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Space-Time Bayesian Compressed Spectrum Sensing for Wideband Cognitive Radio Networks

Space-Time Bayesian Compressed Spectrum Sensing for Wideband...

引用

IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, DySPAN

作者： Zhenghao Zhang Husheng Li Depeng Yang Changxing Pei Department of EECS University of Tennessee Knoxville USA ISN Laboratory Xidian University Shaanxi China

ISBN: (纸本)9781424451890;9781424451883

Wideband spectrum sensing in cognitive radio networks remains an open challenge due to wideband spectrum acquisition implementation. Compressed spectrum sensing provides a powerful approach to acquire wideband signals. We purpose a probabilistic Space-time Bayesian Compressed Spectrum Sensing (ST-BCSS) to combat the noise in wideband compressed spectrum sensing. We present an informative hierarchical prior probabilistic model to recover the compressed spectrum by exploiting the temporal and spatial prior information. These priori information endows the robustness of spectrum sensing subject to noise and low sampling rate. We present a probabilistic framework to address how to represent, convey and fuse multi-prior information to improve the local compressed spectrum reconstruction. Numerical simulation results demonstrate that the ST-BCSS algorithm improves the performance of compressed spectrum sensing under low sampling rate and low Signal Noise Ratio (SNR), compared with the traditional Basis pursuit and Orthogonal Matching pursuit algorithms. A correlation based algorithm for the detection of reconstruction failure due to non-sparse spectrum is also proposed and demonstrated using numerical simulations.

关键词： Bayesian methods Wideband Cognitive radio Matching pursuit algorithms Sampling methods Numerical simulation pursuit algorithms Signal to noise ratio Noise robustness Fuses

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MP-based method on detecting and eliminating the synchronous ECG artifacts in the EEG signals

MP-based method on detecting and eliminating the synchronous...

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The 4th International Conference on Bioinformatics and Biomedical Engineering(第四届IEEE生物信息与生物医学工程国际会议 iCBBE 2010)

作者： Yan-Bo Zhou Pei-Ling Zhou Shi-Min Cai Tao Zhou Department of Electronic Science and Technology University of Science and Technology of China Hefei Department of Electronic Science and Technology University of Science and Technology of China Hefei Department of Physics University of Fribourg P′erolles 1700 Fribourg Switzerland Department of Mo

A method is proposed to detect and eliminate the synchronous ECG artifacts in the EEG Signals based on the matching pursuit algorithm, which doesn’t require the additional synchronous ECG channel or multichannel signals. By using the mixed over-complete dictionary, the EEG signals based on the matching pursuit algorithm are decomposed into atoms. The atoms that have the similar morphological characteristics of R-wave are selected to detect the synchronous ECG R-peak artifacts. Then, the adaptive threshold algorithm is introduced to filter the false detection induced by the morphological characteristics of both ECG artifacts and background EEG signals. At last, the elimination of detected ECG artifacts is realized by the ensemble average subtraction method. By analyzing EEG signals in MIT/BIH database, it presents the excellent result with mean error ratio 1.70%.

关键词： Electrocardiography Electroencephalography Matching pursuit algorithms Signal processing algorithms Dictionaries pursuit algorithms Physics Databases Neurons Cerebral cortex

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Adaptive Inter-Atom Interference Mitigation Approach to Sparse Multi-Path Channel Estimation

Adaptive Inter-Atom Interference Mitigation Approach to Spar...

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IEEE Conference on Vehicular Technology (VTC)

作者： Ruiming Yang Qun Wan Yipeng Liu Wanlin Yang Department of Electronic Engineering University of Electronic Science and Technology Chengdu China

Impulse response of multi-path channel can be estimated by using a short training sequence when the channel is sparse. Though the ordinary orthogonal matching pursuit (OMP) provides fast sparse multi-path channel (SMPC) estimation, it suffers from inter-atom interference (IAI), especially in the case of SMPC with a large delay spread and short training sequence. Herein, an adaptive IAI mitigation method is proposed to improve OMP algorithm based on a sensing dictionary, which is utilized to prevent false atoms from being selected due to serious IAI. Numeral experiments illustrate that the improved OMP algorithm based on adaptive IAI mitigation outperforms both the ordinary OMP algorithm.

关键词： Interference Channel estimation Matching pursuit algorithms Dictionaries Delay estimation Delay effects Wireless communication HDTV Training data pursuit algorithms

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Sparsity enhanced fast subsurface imaging with GPR

Sparsity enhanced fast subsurface imaging with GPR

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Proceedings of the International Conference on Ground Penetrating Radar, GPR

作者： Ali Cafer Gürbüz Department of Electrical and Electronics Engineering TOBB University of Economics and Technology Ankara Ankara Turkey

ISBN: (纸本)9781424446049;9781424446056

Sparsity of a signal starts to become very important in many applications. In subsurface imaging, generally potential targets covers a small part of the total subsurface volume to be imaged, thus the targets are spatially sparse. Under this assumption it is shown that the subsurface imaging problem can be formulated as a dictionary selection problem which can be solved quickly using basis pursuit type algorithms compared to previously published convex optimization based methods. Spatial sparsity also indicates that the number of measurements (spatial or time/frequency) that GPR collects can be reduced, decreasing the data acquisition time. Orthogonal matching pursuit algorithm is used for reconstructing sparse subsurface images. Results show that the proposed method reduces time both in data acquisition and processing compared to previous methods with similar performance.

关键词： Ground penetrating radar Time measurement Data acquisition Matching pursuit algorithms Image reconstruction EMP radiation effects Dictionaries pursuit algorithms Frequency measurement Radar imaging

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An Adaptive Learning Automata Algorithm for Channel Selection in Cognitive Radio Network

An Adaptive Learning Automata Algorithm for Channel Selectio...

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WRI International Conference on Communications and Mobile Computing, CMC

作者： Tran Anh Tuan Lau Chiew Tong A.B. Premkumar School of Computer Engineering Nanyang Technological University Singapore

ISBN: (纸本)9781424463275;9780769539898

Channel selection plays a critical role in cognitive radio networks. In this work, we apply the learning automata techniques to enable a cognitive radio to learn and make decision on channel selection from a set of available channels. The set of randomly available frequency channels is modeled as an unknown environment. As practical networks are usually non-stationary, we propose an adaptive algorithm that enables the cognitive radio to monitor changes in the radio environment and always select the optimal channel after a long run.

关键词： Learning automata Cognitive radio pursuit algorithms Computer networks Mobile communication Mobile computing Adaptive algorithm Monitoring Radio frequency Wireless communication

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Batch algorithms of matching pursuit and orthogonal matching pursuit with applications to compressed sensing

Batch algorithms of matching pursuit and orthogonal matching...

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International Conference on Information and Automation (ICIA)

作者： Huiyuan Wang Jose Vieira Paulo Ferreira Bruno Jesus Isabel Duarte IEETA Universidade de Aveiro Aveiro Portugal School of Information Science and Engineering Shandong University Jinan Shandong China

Batch algorithms of matching pursuit (MP) and orthogonal matching pursuit (OMP) are proposed in this paper. In both algorithms, the original iteration procedures are modified in the following way. Instead of finding a single best-matched atom in each iteration, we find a number of best-matched atoms to speed up the convergence, - a batch version. Then optimized coefficients are computed based on these atoms. Numerical simulations in the application to compressed sensing show that the proposed algorithms are much faster than the original ones, while similar reconstruction precision is obtained.

关键词： Matching pursuit algorithms pursuit algorithms Compressed sensing Image reconstruction Numerical simulation Image coding Image sampling Greedy algorithms Linear systems Automation

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BAYESIAN pursuit ALGORITHM FOR SPARSE REPRESENTATION

BAYESIAN PURSUIT ALGORITHM FOR SPARSE REPRESENTATION

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Zayyani, H. Babaie-Zadeh, M. Jutten, C. Sharif Univ Technol Adv Commun Res Inst Dept Elect Engn Tehran Iran GIPSA Lab Grenoble France

ISBN: (纸本)9781424423538

In this paper, we propose a Bayesian pursuit algorithm for sparse representation. It uses both the simplicity of the pursuit algorithms and optimal Bayesian framework to determine active atoms in sparse representation of a signal. We show that using Bayesian Hypothesis testing to determine the active atoms from the correlations leads to an efficient activity measure. Simulation results show that our suggested algorithm has better performance among the algorithms which have been implemented in our simulations in most of the cases.

关键词： Sparse representation Sparse Component Analysis (SCA) Compressed Sensing (CS) pursuit algorithms

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Ultrasonic Signal Detection Via Improved Sparse Representations

Ultrasonic Signal Detection Via Improved Sparse Representati...

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1st WRI Global Congress on Intelligent Systems (GCIS 2009)

作者： Qi Ai-ling Ma Hong-wei Liu Tao Xian Univ Sci & Technol Sch Comp Sci & Technol Xian 710054 Peoples R China Xian Univ Sci & Technol Sch Mech Engn Xian 710054 Peoples R China Xian Univ Sci & Technol Safety Technol Inst Xian 710054 Peoples R China

ISBN: (纸本)9780769535715

Interference noising originating from the ultrasonic testing defect signal seriously influences the accuracy of the signal extraction and defect location. Sparse signal representations are the most recent technique in the signal processing This technique is utilized to extract casting ultrasonic flaw signals in this paper. But its calculation is huge A new unproved matching pursuit algorithm is proposed Artificial fish swarm algorithm is a stochastic global optimization technique proposed lately. A hybrid artificial fish swarm optimization algorithm based on mutation operator and simulated annealing are employed to search the best atomic. it can greatly reduce complexity of sparse representations Experimental results to detect ultrasonic flaw echoes contaminated by white Gaussian additive noise or correlated noise are presented in the paper. Compared with the wavelet transform. the results show that the signal quality and performance parameters are improved obviously.

关键词： Signal detection Signal processing algorithms Matching pursuit algorithms Marine animals Interference Testing Signal representations Casting pursuit algorithms Stochastic resonance

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Multi-robot Cooperative pursuit Based on Association Rule Data Mining

Multi-robot Cooperative Pursuit Based on Association Rule Da...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Jun Li Qi-shu Pan Bing-rong Hong Mao-hai Li Sch. of Comput. Sci. & Technol. Harbin Inst. of Technol. Harbin China

An approach of cooperative hunting for multiple mobile targets by multi-robot is presented, which divides the pursuiting process into forming the pursuiting groups and capturing the targets. The data sets of attribute relationship is built by consulting many factors about capturing evaders, then the interesting rules can be found by data mining from the data sets to build the pursuiting groups. Through doping out the positions of targets, the members of pursuiting can confirm their destinations. Based on these extensions, a kind of multi-robot cooperative pursuit algorithm that allows dynamic alliance is proposed. The simulation results show that the mobile evaders can be captured effectively and efficiently, and prove the feasibility and validity of the given algorithm under dynamic environment.

关键词： Association rules Data mining Multiagent systems Fuzzy systems Computer science Mobile computing Doping pursuit algorithms Heuristic algorithms Shape

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Reduction of the noise and speckle in Doppler blood flow spectrograms by using matching pursuit with pulse coupled neural network

Reduction of the noise and speckle in Doppler blood flow spe...

引用

Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA

作者： Haiyan Li Yufeng Zhang Dan Xu Zhengyao Bai School of Information Science and Engineering Yunnan University Kunming Yunnan China

To reduce noise and speckles in the spectrograms of Doppler blood flow signals, a novel method, called matching pursuit with pulse coupled neural network (MPPCNN), has been proposed. The method considered is an iterative decomposition algorithm, which decomposes the Doppler ultrasound signals into linear expansion of atoms in a time-frequency dictionary using the matching pursuit (MP) for de-noising the Doppler ultrasound signal. Then, a simplified unidirectional pulse coupled neural network is used to calculate the firing matrix of the de-noised spectrogram. The Doppler speckles of the de-noised spectrogram are located and removed through analyzing and processing the PCNN firing matrix. Experiments were conducted on simulation signals whose SNRs are 0 dB, 5 dB and 10 dB. The result shows that the MPPCNN performs effectively in reducing noise, eliminating Doppler speckles, and enhancing the Doppler spectrograms.

关键词： Noise reduction Speckle Blood flow Spectrogram Matching pursuit algorithms Neural networks Ultrasonic imaging Iterative methods Iterative algorithms pursuit algorithms

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