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IEEE International Conference on Information and Automation (ICIA)

作者： Wei, Shuang Peng, Jian Tao, Chungui Wang, Feng Jiang, Defu Hohai Univ Coll Comp & Informat Array & Informat Proc Lab Nanjing Jiangsu Peoples R China Shanghai Normal Univ Coll Informat Mech & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781538631546

Time delay estimation in multipath environments is important for many applications in the fields of radar, sonar, communication and so on. In this paper, we propose a method based on compressed sensing for time delay estimation. In the proposed method, the signal in time domain is first converted into frequency domain, which tends to convert the problem to a parameter estimation of sinusoidal signals with low flux envelope. Then the corresponding sparse matrix is constructed and the orthogonal matching pursuit (omp) method is used to estimate the time delay parameters. The simulation results show that the proposed algorithm has super-resolution and strong anti jamming, and it performs better than MUSIC algorithm when the time delay parameters are dense distribution in the multipath environments.

关键词： Dense multipath signal compressed sensing time delay estimation omp algorithm

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Improved SVD algorithm for DOA Estimation of Coherent Signal Sources 36

Improved SVD Algorithm for DOA Estimation of Coherent Signal...

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第36届中国控制会议

作者： Ji Zheng-yan Chen Hui Zhang Jia-jia Key Research Laboratory Air Force Early Warning Academy

ISBN: (纸本)9781538629185

In order to solve the coherent problem of Orthogonally Matched(omp) Pursuit algorithm in sparse reconstruction,the feature vector corresponding to large eigenvalue of SVD is constructed by using received data,and two improved methods are *** methods reconstruct the angle through the feature vector,and can reconstruct the angle information accurately without knowingthe number of the signal *** with the classical omp algorithm,the operation speed is faster and the sparse reconstruction effect is *** analysis and simulation results verify the good performance of the algorithm.

关键词： omp algorithm Coherent signal source SVD algorithm

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New Constructions of Bernoulli and Gaussian Sensing Matrices for Compressive Sensing

New Constructions of Bernoulli and Gaussian Sensing Matrices...

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International Conference on Wireless Networks and Mobile Communications (WINCOM)

作者： Nouasria, Hamid Et-tolba, Mohamed INPT Dept Commun Syst Rabat Morocco

ISBN: (纸本)9781538621233

Compressive Sensing (CS) is a new methodology to reconstruct sparse signals from a few number of measurements. These measurements are captured by a sensing matrix, which has a direct impact on the performance of the reconstruction algorithms. Among the sensing matrices proposed in the literature, Bernoulli and Gaussian random sensing matrices are the most prominent. In this work, we propose to improve these two sensing matrices following a trivial method to enhance their columns orthogonality property. Extensive theoretical comparisons with Bernoulli, Gaussian and partial Hadamard sensing matrices are carried out to show the power of the proposed sensing matrices. In that, the new sensing matrices provides a considerable gain in terms of the Rate of Exact Reconstruction (RER).

关键词： Compressive Sensing Sensing Matrix omp algorithm A*omp algorithm

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MMSE-based version of omp for recovery of discrete-valued sparse signals

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ELECTRONICS LETTERS 2016年第1期52卷 75-76页

作者： Sparrer, S. Fischer, R. F. H. Univ Ulm Inst Commun Engn D-89069 Ulm Germany

An enhanced algorithm for the reconstruction of discrete-valued sparse vectors from an underdetermined system of linear equations under the presence of noise is presented. Knowledge from the field of compressed sensing and from digital communications is combined in optimising the estimation step in the orthogonal matching pursuit (omp) algorithm according to the minimum mean-squared error (MMSE) criterion. Thereby, a gain in performance of more than 1 dB is achieved compared with the conventional omp.

关键词： compressed sensing iterative methods least mean squares methods signal reconstruction vectors MMSE criterion omp algorithm compressed sensing digital communications discrete-valued sparse signals discrete-valued sparse vectors reconstruction estimation step linear equations minimum mean-squared error criterion orthogonal matching pursuit algorithm

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Sparse Fusion Based on SAM Elective Sample Dictionary Establishment 13

Sparse Fusion Based on SAM Elective Sample Dictionary Establ...

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IEEE International Conference on Mechatronics and Automation

作者： Sun, Xiaofang Minjiang Coll Dept Geog Fuzhou 350121 Fujian Peoples R China

ISBN: (纸本)9781509023967

In the paper, it is proposed that multi-spectral image pure pixel is utilized for completing SAM classification. The classified samples are utilized for electively constructing sparse dictionary, thereby improving the representativeness of the dictionary. Eight surface feature types are set in Landsat8 image. PPI index is used for calculating pure pixel index of each pixel. Pure pixel of each surface feature is further extracted through N-D visualizer, which is used for SAM calculation. Eight kinds of surface feature samples are selected from SAM image for online dictionary learning. Multi-spectral image sparse dictionary is generated. Multi-spectral image sparse coefficient is calculated through dictionary and omp. Meanwhile, online dictionary and omp are utilized for obtaining panchromatic image sparse coefficient. Fusion sparse coefficient is generated by maximum values both sparse coefficients. Multi- spectral image sparse dictionary is combined for reconstructing and generating fusion image. Eight quantitative fusion evaluation indicators are adopted for comparing algorithm fusion and weighted fusion in the paper. Fusion method proposed in the paper contains more information, fusion image texture detail information is improved, and better image multi-spectral information is kept.

关键词： Sparse dictionary Online dictionary learning algorithm omp algorithm SAM

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Cascaded clutter and jamming suppression method using sparse representation

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ELECTRONICS LETTERS 2015年第19期51卷 1524-1525页

作者： Feng, Weike Zhang, Yongshun He, Xingyu Guo, Yiduo Air Force Engn Univ Xian 710051 Shaanxi Peoples R China

To suppress ground clutter and barrage noise jamming for airborne radar effectively and efficiently, a cascaded method using the sparse representation technique is proposed. Based on the sparsity of jamming in the spatial domain, the jamming subspace is first estimated using the orthogonal matching pursuit algorithm with only one snapshot. Then, the jamming is rejected by projecting the received signal on the orthogonal complement subspace of the jamming. Lastly, reduced-dimension space-time adaptive processing algorithms are utilised directly to suppress clutter. Simulation results demonstrate that the novel method could achieve great performance as well as a significant saving of computation and training samples.

关键词： airborne radar approximation theory jamming signal representation space-time adaptive processing omp algorithm RD-STAP algorithms airborne radar cascaded clutter method jamming suppression method orthogonal matching pursuit algorithm reduced-dimension space-time adaptive processing algorithms sparse representation technique spatial domain

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Suppression of LFM interference in direct sequence spread spectrum communications based on compressive sensing 5

Suppression of LFM interference in direct sequence spread sp...

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IEEE International Conference on Signal Processing, Communications and Computing ICSPCC 2015

作者： Zhang Yongshun Jia Xin Zhu Weigang Equipment Acad Beijing Peoples R China

ISBN: (纸本)9781479989201

The existing linear frequency modulation (LFM) interference suppression algorithms for direct sequence spread spectrum (DSSS) communications are confined to the high sampling rate In order to solve the problem, compressive sensing (CS) was applied to suppress the LFM interference in DSSS communications. The DSSS signal sparse dictionary and LFM interference waveform matching dictionary was built. The algorithm was designed to suppress the LFM interference in compressed domain by using the orthogonal matching pursuit (omp) algorithm The effectiveness of the algorithm was validated by computer simulation. The simulation results show that the algorithm could suppress the LFM interference effectively, interference suppression effect don't change with the interference intensity and interference position. This will provide an effective method for the reconstruction of the compressed DSSS signal in the condition of the LFM interference.

关键词： CS LFM interference suppression DSSS communications sparse dictionary omp algorithm

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Research on MompDES algorithm of block cipher in compressed sensing 6

Research on MOMPDES algorithm of block cipher in compressed ...

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6th International Conference on Electronics and Information Engineering (ICEIE)

作者： Deng Hubin Zhou Jie Chen Rong Hu Ruifeng E China Jiaotong Univ Dept Coll Informat Engn Nanchang 330013 Peoples R China Dept TELLHOW SCI TECH CO Nanchang 330029 Peoples R China

ISBN: (纸本)9781510600294

According to the design of block cipher algorithm thought the current mainstream, DES block cipher algorithm based on compressed sensing, combined with the design idea of omp algorithm, proposed a design of the block cipher Momp-DES. We discussed the design of MompDES algorithm, the whole process, and encryption and decryption algorithms. It introduces the security of MompDES briefly and is simulated by the experiment, the results prove the recovery error is very small after decryption, and we can get a complete plaintext.

关键词： Compressed Sensing omp algorithm Block Cipher DES algorithm MompDES algorithm

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Design and Implementation of Restoration techniques for Audio denoising applications

Design and Implementation of Restoration techniques for Audi...

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IEEE Recent Advances in Intelligent Computational Systems (RAICS)

作者： Mathai, Merin K. Deepa, J. Coll Engn Dept Elect Chengannur India

ISBN: (纸本)9781467366700

Speech and music signals are mainly subject to localized and globalized degradations. Localized distortions, such as clipping, and clicks, due to old recordings or scratched CDs where the intervals of distorted samples are surrounded by undistorted samples. Globalized degradation such as broadband noise, where whole samples are affected by noise. Audio restoration is a technique for restoring the audio signals from these distortions. In this paper, audio restoration techniques for removing clipping, clicks and broadband noise are defined. Recent approaches to solving audio restoration problem is with respect to sparse representation algorithms. Clipping distortion is addressed with a Sparse representation framework, it is treated as an inverse problem, where one observes un-clipped samples while the missing samples to be estimated for that, they are embedded in frame based scheme, and reconstructed by using an OLA approach in conjunction with omp algorithm using Gabor/DCT dictionary. Broadband denoising is done by using spectral subtraction method. Click removal is done by using the basics of adaptive signal processing. Performance measures are done based on perception, average SNR calculation and defined parameter variations. This paper also targeting towards the software and hardware implementation of the restoration methods using TMS320C6713 DSK kit with help of tools mainly MATLAB and Code Composer studio.

关键词： Audio Distortions omp algorithm Gabor/DCT dictionary TMS320C6713DSK

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A new mathematics method for structural health monitoring's damage detection based on WSNs 1

A new mathematics method for structural health monitoring's ...

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1st International Conference on Computational Intelligence Theory, Systems and Applications (CCITSA)

作者： Ji, Sai Yang, Ping Sun, Yajie Shen, Jian Wang, Jin Nanjing Univ Informat Sci & Technol Educ Minist Demonstrat Base Internet Applicat Inn Nanjing Jiangsu Peoples R China Yangzhou Univ Sch Informat Engn Yangzhou Jiangsu Peoples R China

ISBN: (纸本)9781467386005

In the Wireless Sensor Network (WSN) for structural health monitoring (SHM), usually, we transmit the original acquisition data and exchange the large amounts of data between nodes which consume huge energy, occupy a large amount of communication bandwidth. Thus, data compression or data fusion to reduce network traffic and energy loss before transmission is necessary. In this work, we established a suitability compressive sensing (CS) to address some challenges in the Aviation Aluminum Plate Structural Health Monitoring System (AAPSHM) using WSN. Through the experimental demonstration, the application of this method could ensure the accuracy of the data as well as balance the network energy consumption. And it can also reduce the cost of data storage and transmission, improve the efficiency and make a certain contribution to the quality for the AAPSHM.

关键词： compressive sensing structural health monitoring data compression the measurement matrix omp algorithm AAPSHM

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