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Compressed sensing theory analysis

Author: DuanFei
Tutor: LiSong
School: Zhejiang University
Course: Applied Mathematics
Keywords: Compressed Sensing Sparsity Compressibility Sparse Representation Reconstruction Algorithm
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 288
Quote: 1
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Abstract


Compressed sensing is a new theory of information acquisition , it broke through the traditional sampling theory , data acquisition and data compression combined reconstruction algorithm to restore the original data . Traditional sampling process , in order to avoid signal distortion, according to the the Shannon-Nyqusit theorem , the sampling rate should not be less than twice the highest frequency of the signal , which makes in obtaining the data of the digital signal , it will lead to a large number of sampling data , and reduces the efficiency of the data processing and compression sensing theory using non self - adaptive linear projection of the original signal to obtain the information, and then through the numerical optimization problem to reconstruct the original signal which makes the amount of data of the compressed sample is far less than the amount of data required by the traditional sampling theory . Therefore , this theory concern in the field of signal and image processing , and has a broad application prospects . compressed sensing theory of a late start, there are a lot of issues and direction worthy of our in-depth studies , many researchers study focused on the part of the reconstruction algorithm . the reconstruction algorithm is the core part of the compressed sensing theory are of great significance to verify the accuracy of the reconstruction of the signal , and the sampling process compressed paper introduces the basic knowledge of the theory of compressed sensing , and major reconstruction algorithm is mainly depth study and analysis of contents of several existing classical reconstruction algorithm Finally, each of a given signal and random signal , for example , data to achieve a series of algorithms and iterative threshold algorithm based on greedy algorithm , and gives algorithm analysis and achieve results .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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