摘要
混沌特性的识别是对非线性时间序列进行分析、预测、控制的基础。本文克服了已有文献用Lya-punov指数识别混沌时计算Lyapunov指数的不足,由关联积分构造统计量来计算相空间重构的参数,然后利用混沌的遍历性及定义,提出了计算最大Lyapunov指数的新方法。
The foundation of analysis, prediction and control to nonlinear time series is how to identify chaos.In this paper the drawback of using. Lyapunov exponents to identify chaos is overcome on old methods in some literature for calculating Lyapunov exponents. First, we utilize the statistics constructed from correlation dimension to estimate parameters in the phase space reconstruction. Then, according to the ergodicity of chaos and the definition of Lyapunov exponents, we put forward a new method for calculating the largest Lyapunov exponent.
出处
《系统工程理论方法应用》
2003年第4期317-320,共4页
Systems Engineering Theory·Methodology·Applications
