Compressed Sensing Noisy Signal Reconstruction System Based on Singular Value Decomposition

A singular value decomposition and compressed sensing technology, which is applied in the field of compressed sensing noisy signal reconstruction system, can solve the problem of low reconstruction accuracy of compressed sensing noisy signal

Active Publication Date: 2011-12-21
HUNAN UNIV
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Problems solved by technology

[0004] In order to overcome the defect of low reconstruction accuracy of compressed sensing noisy signal, the present invention provides a compressed sensing noisy signal reconstruction system based on singular value decomposition with high reconstruction accuracy

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  • Compressed Sensing Noisy Signal Reconstruction System Based on Singular Value Decomposition

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Embodiment Construction

[0028] The present invention will be further described below in conjunction with the examples.

[0029] This embodiment includes

[0030] (1) The initial module of system operation, that is, the initial interface of system operation;

[0031] (2) Compression module, the user selects the original signal that needs to be compressed, and uses the improved observation random matrix to compress the original signal. The compression of the original signal is realized by multiplying the original signal and the improved observation random matrix, and the improved observation random matrix is ​​realized. The matrix is ​​a new observation random matrix after the singular value of the random matrix is ​​modified by the maximum entropy algorithm, and the compressed perception signal is saved;

[0032](3) Reconstruction module, which is used by the user to reconstruct the original signal from the selected compressed perceptual signal through the reconstruction algorithm. The reconstructed ...

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Abstract

The invention discloses a singular value decomposition-based compressed sensing noisy signal reconfiguration system, which comprises (1) an initial module for running the system, namely an initial interface for running the system, (2) a compression module and (3) a reconfiguration module, wherein an original signal to be compressed is selected by using the compression module by a user; data compression is performed on the original signal by using an improved observation random matrix; the compression of the original signal is realized by multiplying the original signal by the improved observation random matrix; a compressed sensing signal is stored; the selected and compressed sensing signal is reconfigured by using the reconfiguration module by the user through a reconfiguration algorithm to form the original signal; the reconfigured original signal is a reconfigured signal; and meanwhile, the reconfiguration accuracy of the original signal and the reconfigured signal is obtained. The system has high reconfiguration accuracy, superior robustness and a wide application range.

Description

technical field [0001] The present invention relates to a compressive sensing noisy signal reconstruction system, in particular to a compressive sensing noisy signal reconstruction system based on singular value decomposition. Background technique [0002] Compressed Sensing (CS) theory was first proposed by Cands, Romberg, Tao, and Donoho in 2004. It is a novel signal processing theory that has emerged in recent years. It uses information sampling to process sparse signals. . Based on this theory, the number of sampling requirements for reconstructing the signal can be much lower than the dimension of the observation, breaking the traditional Nyquist sampling theorem. Its theory contains three core issues: signal sparse transformation, observation matrix design and reconstruction algorithm. Donoho gave three conditions that the observation matrix must have, and pointed out that most of the random matrices with uniform distribution have these three conditions and can be us...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03M7/40
Inventor 何怡刚彭玉楼彭玉旭
Owner HUNAN UNIV
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