MODELING AND SIMULATING HIGHER DIMENSIONAL CHAOTIC DATA

被引：2

作者：

GORA, P

BOYARSKY, A

机构：

[1] Department of Mathematics Concordia University, H4B 1R6, Loyola Campus Montreal

来源：

COMPUTERS & MATHEMATICS WITH APPLICATIONS | 1992年 / 24卷 / 11期

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

10.1016/0898-1221(92)90035-G

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

We consider time series data whose estimated Lyapunov exponents are positive. This data is represented by a probability density function on a suitably fine partition of the phase space. An algorithm is presented for constructing a transformation tau which has a unique absolutely continuous invariant measure whose density function is f and which has the same Lyapunov exponents as the original time series. An example is given.

引用

页码：101 / 105

页数：5

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