A new method to estimate the Kolmogorov entropy from recurrence plots: its application to neuronal signals

被引：97

作者：

Faure, P ^{[1
]}

Korn, H ^{[1
]}

机构：

[1] Inst Pasteur, INSERM, U261, F-75724 Paris 15, France

来源：

PHYSICA D | 1998年 / 122卷 / 1-4期

关键词：

chaos; Kolmogorov-Sinai entropy; recurrence plot; synaptic noise; neuron;

D O I：

10.1016/S0167-2789(98)00177-8

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

Recurrence plots are a useful graphic tool for studying dynamical systems. A new variable is proposed to quantify their deterministic structure. It allows an easy computation of the KZ entropy since the distance between points needs to be calculated only once instead of every time for each new embedding dimension, and it bypasses some of the Limitations inherent to the classical Grassberger and Procaccia method. It is valuable for biological data, as illustrated here by tests with various dynamical models and its application to experimental signals recorded from neurons. (C) 1998 Elsevier Science B.V.

引用

页码：265 / 279

页数：15

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[21] FILTERED NOISE CAN MIMIC LOW-DIMENSIONAL CHAOTIC ATTRACTORS [J].