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3下载：
陆吾生教授是加拿大维多利亚大学电气与计算机工程系的教授。此课件为其在国内大学短期精品课程的课件。包含最优化问题求解，压缩感知方法及其在稀疏信号和图像处理中的应用（压缩、重构、降噪等）。-Professor Lu Wusheng University of Victoria, Canada Professor of Electrical and Computer Engineering. The courseware for the University in the domestic short
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用MATLAB实现的压缩传感，外文资料，里面含有部分源代码，用MATLAB可以仿真-Compressed sensing using MATLAB implementation, foreign language data, which contains part of the source code can be simulated using MATLAB
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基于压缩感知的图像处理，分别使用二维DCT、FFT和一维dwt变换对图像信号进行稀疏变换，然后使用正交匹配追踪算法进行重构，在进行相应的逆变换-This is a image processing procedure based on compressed sensing which respectively uses two-dimensional DCT, FFT and one-dimensional dwt transform to sparse the image signal a
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采用KSVD算法通过训练的方法来构造稀疏过完备字典，在使用时一定要确保已装有ompbox9。可用于语音，图像信号处理等的稀疏字典构造-KSVD algorithm using the method of training to construct the sparse over-complete dictionary, in use, make sure have been installed ompbox9. Can be used for the sparse dictionary cons
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Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing，稀疏表示的最新巨作-Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing, sparse representation of the latest blockbuster
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This set of MATLAB files contain an implementation of the gradient projection algorithms described in the paper "Gradient Projection for Sparse Reconstruction: Application to Compressed Sensing and Other Inverse Problems" by Mario A. T. Figueiredo, R
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一个很有用的基于稀疏的信号处理工具箱，包含有多种算法。-a useful toolbox based on sparse signal processing
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这是Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing书中对应的实现程序，对理解书中所讲理论有很好的帮组，这本书是学习稀疏编码和压缩感知的一本很好的书-Sparse and Redundant Representations From Theory to Applications in Signal and Image Processing book cor
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这是线性训练K-SVD词典的一种新算法
表示的信号。给定一组信号，K-SVD试图
提取物，可以稀疏表示这些信号最好的词典。
深入讨论了K-SVD算法中可以找到的：
“K-SVD：设计的超完备字典的一个算法
稀疏表示”，由M.阿哈，M. Elad和点写，适应性，
在IEEE Transactions出现。在信号处理，卷54，11号，
第4311-4322，十一月2006。-he K-SVD is a new algorithm
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信号的稀疏表示,它意欲用尽可能少的非0系数表示信号的主要信息,从而简化信号处理问题的求解过程-Signal sparse representation, it intends to as little as possible of non-zero coefficient signal is the main information, so as to simplify the solving process of signal processing problems
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陆吾生教授短期课程“压缩感知方法及其在稀疏信号和图像处理中的应用”资料，使用的源码，有参考价值-Professor Lu Wusheng Short Course " compressed sensing method and the sparse signal and image processing applications," the source data, the use of a reference value
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阵列信号处理，空间谱估计，利CVX工具箱实现稀疏重构的单快拍DOA估计-Array signal processing, spatial spectrum estimation, and CVX toolbox to achieve the sparse reconstruction of single snapshot DOA estimation
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信号稀疏表示是一种新兴的信号分析和综合方法，其目的就是在过完备字典中用尽可能少的原子来表示信号。采用时频原子字典的信号稀疏表示能够有效地揭示非平稳信号的时变特征。信号稀疏表示吸引了研究者的大量关注，这种方法已经被应用到信号处理的许多方面，例如非平稳信号分析，信号编码、识别与信号去噪等。-Signal sparse representation is a new method of signal analysis and synthesis, and its purpose is in over-
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阵列信号处理方面，基于相关矩阵的稀疏重构，利用cvx工具箱求解；DOA估计(In array signal processing, sparse reconstruction based on correlation matrix is solved by CVX toolbox, and DOA estimation is used)
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用于稀疏优化的最新非凸函数GMC算法，可用于信号处理以及图像处理。(The latest non convex function GMC algorithm for sparse optimization, can be used for signal processing and image processing.)
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信号稀疏表示的目的就是在给定的超完备字典中用尽可能少的原子来表示信号，可以获得信号更为简洁的表示方式，从而使我们更容易地获取信号中所蕴含的信息，更方便进一步对信号进行加工处理，如压缩、编码等(Signal sparse representation is to overcomplete dictionary given in as little as possible to represent atomic signal, signal can be more succinct represen
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MATLAB implementation of compressive sensing example as described in R.
Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118],
July 2007. The code acquires 250 averaged random measurements of a 2500
pixel image. We assume that the ima
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MATLAB implementation of compressive sensing example as described in R.
Baraniuk, Compressive Sensing, IEEE Signal Processing Magazine, [118],
July 2007. The code acquires 250 averaged random measurements of a 2500
pixel image. We assume that the
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Sparse signal processing algorithms
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阵列信号处理，采用遗传算法对阵列进行稀疏化处理，对于研究阵列天线的学者有帮助(Array signal processing and sparse processing with genetic algorithm are helpful to scholars who study array antenna.)
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