CONVERGENCE-RATES AND DATA REQUIREMENTS FOR JACOBIAN-BASED ESTIMATES OF LYAPUNOV EXPONENTS FROM DATA

被引：89

作者：

ELLNER, S ^{[1
]}

GALLANT, AR ^{[1
]}

MCCAFFREY, D ^{[1
]}

NYCHKA, D ^{[1
]}

机构：

[1] N CAROLINA STATE UNIV,DEPT STAT,RALEIGH,NC 27695

来源：

PHYSICS LETTERS A | 1991年 / 153卷 / 6-7期

关键词：

D O I：

10.1016/0375-9601(91)90958-B

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

We present a method for estimating the dominant Lyapunov exponent from time-series data, based on nonparametric regression. For data from a finite-dimensional deterministic system with additive stochastic pertubations, we show that the estimate converges to the true values as the sample size increases, and give the asymptotic rate of convergence.

引用

页码：357 / 363

页数：7

共 45 条

[1] PREDICTION IN CHAOTIC NONLINEAR-SYSTEMS - METHODS FOR TIME-SERIES WITH BROAD-BAND FOURIER SPECTRA [J].