DocumentCode :
2521503
Title :
A blind identify algorithm for weak signals in chaotic noise
Author :
Wang Yingchun ; Zhou Yefei ; Zhou Chenghua
Author_Institution :
Manage. Sch., Tianjin Univ. of Technol., Tianjin, China
fYear :
2009
fDate :
10-11 Oct. 2009
Firstpage :
388
Lastpage :
391
Abstract :
For a kind of weak harmonic wave signal in chaotic noise, this paper proposes a new blind identify algorithm which based on generalized regression neural network (GRNN) to estimate parameters of chaotic system, and then apply reiteration blind deconvolution method to remove remains noise in the system, and extract weak signal from chaotic background. From 2597 observation points, we obtain mean deviation as 0.0112, and peak value signal-noise ratio as -44.77 dB. Simulation result shows efficiency of the algorithm.
Keywords :
deconvolution; iterative methods; neural nets; regression analysis; signal detection; blind identify algorithm; chaotic noise; generalized regression neural network; reiteration blind deconvolution method; signal detections; weak signals; Background noise; Chaos; Chaotic communication; Data mining; Deconvolution; Frequency; Neural networks; Signal detection; Signal processing; White noise; chaotic system; neural network; reiteration blind deconvolution; signal detection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery, 2009. CyberC '09. International Conference on
Conference_Location :
Zhangijajie
Print_ISBN :
978-1-4244-5218-7
Electronic_ISBN :
978-1-4244-5219-4
Type :
conf
DOI :
10.1109/CYBERC.2009.5342187
Filename :
5342187
Link To Document :
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