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.
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页码：101 / 105
页数：5
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