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.
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)
关键词
盲反卷积
混沌
信号处理
blind deconvolution
chaos
signal processing
