基于局域波分解的混沌时间序列分析  

Chaos Time Series Analysis Based on Local Wave Decomposition

作　　者：周波[1] 李楠[1] 张海勇[2] 

机构地区：[1]大连舰艇学院基础部,大连116018 [2]大连舰艇学院信息工程系,大连116018

出　　处：《系统仿真学报》2007年第22期5291-5293,共3页Journal of System Simulation

基　　金：国家自然科学基金项目(60472109)

摘　　要：采用希尔伯特谱方法分析混沌信号的瞬时频率,揭示混沌信号的各组成成分的频率随时间变化的规律;针对噪声背景下的混沌信号降噪问题,以Lorenz方程为例,采用局域波分解方法对含噪信号进行自适应滤波。通过与小波去噪方法对比,仿真结果表明局域波方法的算法通用性强,降噪效果好。The instantaneous frequency of chaos time series was analyzed by using Hilbert Spectrum, which revealed the intrinsic time-frequency characteristics of chaotic signals. To solve the de-noising problem, the Local Wave Decomposition （LWD） method was adopted because of its adaptive filter characteristic by taking Lorenz equation as an example. The simulation result shows the LWD is more suitable for extracting chaotic signal by comparing with wavelet.

关 键 词：混沌信号 局域波分解 瞬时频率 小波分析 降噪 

分 类 号：TH17[机械工程—机械制造及自动化] TN911.7[电子电信—通信与信息系统]