混沌卷积混合信号的预测重构盲反卷积方法  

A blind deconvolution method for chaotic signals based on prediction and recons truction analysis

作　　者：成谢锋[1] 陈鹤鸣[1] 马勇[2] 黄勇林[1] 

机构地区：[1]南京邮电大学光电工程学院 [2]北京机械工业学院基础部,北京100085

出　　处：《智能系统学报》2007年第4期63-68,共6页CAAI Transactions on Intelligent Systems

基　　金：山东省自然科学基金资助项目(y2006G03);山东省重点科技攻关项目(2006Gg204005)

摘　　要：介绍了混沌序列的特性,然后利用混沌的类随机特性和盲信号处理技术,提出了一种针对混沌卷积混合信号的预测重构盲反卷积方法.该方法充分利用了混沌的物理特性,通过对混沌卷积混合信号使用基于直接预测误差分析所构成的混沌滤波器和基于相空间重构动力学系统方程的人工智能补偿技术去进行盲反卷积,从而实现对单输入单输出混沌卷积信号的源信号和传输函数的盲反卷积处理.仿真实验验证了该方法的有效性和可行性.Based on the statistical characteristics of chaotic signals and blind signal processing techniques, a blind deconvolution method for chaotic signals based on prediction and reconstruction analysis is proposed. This method achieves blind deconvolution with respect to source signals and transmission functions of chaotic signals with single-input and single-output through linear predication error analysis and artificial intelligence compensation. The effectiveness and feasibility of the proposed method were demonstrated in s lations.

关 键 词：盲反卷积 混沌 信号处理 

分 类 号：TN911[电子电信—通信与信息系统]