Open AccessA parameter optimization nonlinear adaptive denoising algorithm for chaotic signals
Author(s) -
Mengjiao Wang,
Zhang Wu,
Jufu Feng
Publication year - 2015
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.64.040503
Subject(s) - chaotic , autocorrelation , noise reduction , algorithm , window (computing) , nonlinear system , noise (video) , computer science , signal (programming language) , residual , window function , mathematics , artificial intelligence , physics , statistics , image (mathematics) , computer vision , quantum mechanics , programming language , operating system , filter (signal processing)
In the parameter optimization issue of nonlinear adaptive denoising algorithm for chaotic signals, the window length is affected by different factors. In this paper, a criterion is proposed for selecting the optimal window length. According to the difference in autocorrelation function between chaotic signal and noise, first, the different window sizes are used for denoising noisy chaotic signals. Then, the residual autocorrelation degree (RAD) of each window length is computed. Finally, the optimal window length is obtained by shrinking the window length corresponding to the minimum RAD. Simulation results show that this criterion can automatically optimize the window length efficiently under different conditions, which improves the adaptivity of the denoising algorithm of chaotic signals.