ISSN: 0973-7510

E-ISSN: 2581-690X

Ma Yong1 , Tang Zhenmin1 and Tao Yewei2
1School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, Jiangsu – 210 094, China.
2College of Mathematics and Physics, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu – 200 03, China.
J Pure Appl Microbiol. 2013;7(Spl. Edn.: April):397-403
© The Author(s). 2013
Received: 03/03/2013 | Accepted: 14/04/2013 | Published: 30/04/2013

EEG signal has the chaotic character. After studying the statistic characteristics of chaotic signals, a deconvolution filter for chaotic signal is introduced by the linear predication error analysis. Based on the chaotic geometric characteristic, the output data of this filter are used to reconstruct the dynamical equation of the original chaotic signal. Then the output data are corrected according to the chaotic physical feature. So a blind deconvolution method is achieved successfully which has single-input and single-output chaotic convolution mixed signal. And EEG signal simulation result verified the effectiveness of this proposed method.


Blind deconvolution, chaos, linear predication, phase space reconstitution, EEG

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