Adaptive Noise Reduction Algorithm for Chaotic Signals Based on Wavelet Packet Transform

被引：0
|
作者：
Liu Y. [1 ]
Bei G. [1 ]
Jiang Z. [1 ]
Meng Q. [1 ]
Shi H. [1 ]
机构：
[1] Engineering Training Center, Shandong University of Science and Technology, Qingdao
来源：
Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology | 2023年 / 45卷 / 10期
关键词：
Chaos; Local projection; Neural network; Noise reduction; Wavelet packet;
D O I：
10.11999/JEIT221137
中图分类号：
学科分类号：
摘要：
To reflect better the inherent characteristics of chaotic systems, an adaptive noise reduction algorithm for chaotic signals based on wavelet packet transform is proposed. Firstly, the best decomposition level is determined according to the different correlation of wavelet packet coefficients in different decomposition scales, while the optimal wavelet packet basis is obtained with the logarithmic energy entropy as the cost function. Then, the approximate coefficients are projected in the local neighborhood and the detail coefficients are adaptively selected with the gradient descent algorithm in neural network. By minimizing the loss function, the influence of noises on chaotic signals is reduced to the greatest extent. Finally, simulations on the state variables originating from Rossler chaotic model verify the denoising superiority of the proposed algorithm for the chaotic signals. © 2023 Science Press. All rights reserved.
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页码：3676 / 3684
页数：8
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