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Algorithm integrated with forward backward pursuit and based on compression perception theory

A matching tracking and compressed sensing technology, applied in computing, computer components, instruments, etc., can solve the problem of low sampling rate and achieve the effect of improving algorithm performance

Inactive Publication Date: 2017-05-10
NANKAI UNIV
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Problems solved by technology

Especially when the sparseness of the signal to be acquired is relatively high, the sampling rate required by this scheme is much lower than the traditional Nyquist sampling theorem

Method used

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  • Algorithm integrated with forward backward pursuit and based on compression perception theory
  • Algorithm integrated with forward backward pursuit and based on compression perception theory
  • Algorithm integrated with forward backward pursuit and based on compression perception theory

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Embodiment Construction

[0030] In order to express the embodiments, significance and advantages of the present invention more clearly, the present invention will be described in more detail below in conjunction with the accompanying drawings and comparison diagrams of reconstruction effects.

[0031] figure 1 It is an algorithm flow chart of forward and backward matching and tracking based on compressed sensing fusion proposed by the present invention. The specific flow of the algorithm is as follows:

[0032] (1) Input: perception matrix Φ, measurement value y, forward step size α, backward step size β 1 and beta 2 , the maximum limit parameter K of the support set max , residual energy termination parameter ε, support set retention control parameter η;

[0033] (2) Initialization: initial support set initial residual r 0 = y, the initial number of iterations k = 0;

[0034] (3) The perception matrix Φ, the measured value y, the forward step size α, and the backward step size β 1 and the emp...

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Abstract

The invention discloses an algorithm integrated with forward backward pursuit and based on a compression perception theory and belongs to the compression perception signal processing field. A traditional forward backward pursuit algorithm optimizing a single algorithm operation parameter to improve a reconstruction effect is replaced, a new visual angle of the fusion strategy is utilized to improve algorithm reconstruction performance; the useful information of a failure algorithm is utilized and is applied to a same algorithm of different parameters; any other prior information is not required, only the information of the same algorithm of different parameters is utilized to improve the algorithm reconstruction effect. The method is advantaged in that the method is better in accurate reconstruction probability and average reconstruction errors of sparse signals compared with the traditional forward backward pursuit algorithm, and actual application capability of the compression perception theory can be effectively improved.

Description

[0001] 【Technical field】 [0002] The invention relates to an algorithm based on compressed sensing fusion forward and backward matching and tracking, and belongs to the technical field of compressed sensing signal processing. [0003] 【Background technique】 [0004] From the perspective of reducing the sampling rate and complexity of the actual measurement system, compressed sensing effectively combines the two processes of sampling and compression of sparse signals. Assuming that the final signal to be obtained is sparse or sparse after a certain matrix transformation, then compressed sensing can provide a new low-energy sampling scheme. Especially when the sparseness of the signal to be acquired is relatively high, the sampling rate required by this scheme is much lower than the traditional Nyquist sampling theorem. The characteristic of this low sampling rate makes compressed sensing have broad application prospects in wireless sensor networks, nuclear magnetic resonance i...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H03M7/30G06K9/62
CPCH03M7/3062H03M7/55G06F18/2133G06F18/2136G06F18/25
Inventor 孙桂玲王锋李洲周郑博文
Owner NANKAI UNIV
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