Application of local polynomial estimation in suppressing strong chaotic noise |
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Authors: | Su Li-Yun Ma Yan-Ju Li Jiao-Jun |
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Affiliation: | School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China;School of Mathematics and Statistics, Chongqing University of Technology, Chongqing 400054, China;School of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China |
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Abstract: | In this paper, we propose a new method that combines chaotic series phase space reconstruction and local polynomial estimation to solve the problem of suppressing strong chaotic noise. First, chaotic noise time series are reconstructed to obtain multivariate time series according to Takens delay embedding theorem. Then the chaotic noise is estimated accurately using local polynomial estimation method. After chaotic noise is separated from observation signal, we can get the estimation of the useful signal. This local polynomial estimation method can combine the advantages of local and global law. Finally, it makes the estimation more exactly and we can calculate the formula of mean square error theoretically. The simulation results show that the method is effective for the suppression of strong chaotic noise when the signal to interference ratio is low. |
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Keywords: | strong chaotic noise local polynomial estimation weak signal detection |
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