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Independent components analysis (ICA) blind signal separation method and system based on smoothing function and Parzen window estimation

A blind signal separation and function technology, applied in the field of blind signal processing, can solve problems such as the difficulty of non-parametric estimation of the probability density function

Inactive Publication Date: 2011-05-25
NANJING UNIV
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Problems solved by technology

[0005] The technical problem to be solved in the present invention is: the estimation of the probability density function of source signal is very important to ICA blind signal separation, the non-parametric estimation of probability density function is very difficult, needs a kind of effective ICA blind signal separation method

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  • Independent components analysis (ICA) blind signal separation method and system based on smoothing function and Parzen window estimation
  • Independent components analysis (ICA) blind signal separation method and system based on smoothing function and Parzen window estimation
  • Independent components analysis (ICA) blind signal separation method and system based on smoothing function and Parzen window estimation

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Embodiment Construction

[0083] The specific implementation manner of the present invention will be described below in conjunction with the accompanying drawings and technical solutions.

[0084] The system of ICA blind signal separation method based on polishing function and Parzen window estimation includes a receiving signal module, a signal preprocessing module, a NewICA reconstruction source signal module, and a subsequent processing module, with NewICA reconstruction source signal as the core module, the present invention The separation method of is carried out in the NewICA reconstruction source signal module.

[0085] Such as figure 1 As shown, the receiving signal module completes sampling the source signal sent by the sending end to obtain the observation signal. At this time, for the receiving end, the source signal, transmission channel, etc. are all unknown. The observed signal is an independent source signal, which is obtained after channel mixing and doping with channel noise.

[008...

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Abstract

The invention discloses an independent components analysis (ICA) blind signal separation method and an ICA blind signal separation system based on a smoothing function and Parzen window estimation. A new ICA blind signal separation method is provided on the basis of Parzen window estimation technology assisted by a newly constructed smoothing function, so that a probability density function and a hybrid matrix of a source signal are estimated, and an unknown blind source signal is effectively separated out. A corresponding separation system comprises a signal receiving module, a single preprocessing module, a NewICA reconstruction source signal module and a subsequent processing module which are connected in turn. An effective ICA blind signal separation method and an effective ICA blind signal separation system with small error and high signal to interference ratio are provided.

Description

technical field [0001] The invention belongs to the field of blind signal processing, and particularly relates to techniques such as polishing function, maximum likelihood function, Parzen window estimation, quasi-Newton iteration, minimum mutual information entropy, independent component analysis, blind signal separation, etc. ICA Blind Signal Separation Method and System Based on Function and Parzen Window Estimation. Background technique [0002] Blind signal processing refers to extracting the target signal of interest by using the signal source separation method in the case of unknown transmission channel and source signal information in a mixed scene. It specifically includes blind separation of independent sources, blind deconvolution, and blind identification. It is an adaptive array signal processing method with good tolerance to signal source knowledge and channel prior knowledge, even if no signal source information and channel information are known. In the case ...

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Application Information

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IPC IPC(8): H04L25/03
Inventor 成孝刚安明伟李勃陈启美唐岚高艳宁
Owner NANJING UNIV
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