电子学报2011，Vol.39Issue(1)：13-17,5.
基于双提升小波的自适应混沌信号降噪
Adaptive Noise Reduction for Chaotic Signals Based on Dual- Lifting Wavelet Transform
摘要
Abstract
According to different characteristics of chaotic signals and Gaussian noises, an adaptive noise reduction method is proposed based on dual-lifting wavelet. Singular spectrum analysis (SSA) and gradient decent algorithm are respectively used for the analysis of coarse approximation and detail information. The former removes smaller singular value representing noises in a greater degree, while the latter employed for the adaptive choice of wavelet coefficients further improves the positioning accuracy of signals. The chaotic signals generated by Lorenz model as well as the observed monthly series of sunspots are applied for simulation analysis, the numerical experiment results confirm that the adaptive method in this paper is effective for noise reduction of chaotic signals.关键词
双提升小波/奇异谱分析/梯度下降算法/混沌信号/降噪Key words
dual-lifting wavelet/singular spectrum analysis/gradient decent algorithm/chaotic signals/noise reduction分类
信息技术与安全科学引用本文复制引用
刘云侠,杨国诗,贾群..基于双提升小波的自适应混沌信号降噪[J].电子学报,2011,39(1):13-17,5.基金项目
淮南师范学院青年科学研究项目(No.2010QNL15) （No.2010QNL15）
