Spectral and wavelet methods for the analysis of nonlinear and nonstationary time series

被引：17

作者：

Rao, TS

Indukumar, KC

机构：

[1] Department of Mathematics, University of Manchester, Institute of Science and Technology

[2] CMC Ltd., R and D Centre, Gachibowli, Hyderabad

来源：

JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 1996年 / 333B卷 / 03期

关键词：

D O I：

10.1016/0016-0032(96)00011-7

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Higher order spectral methods are widely used to analyse stationary nonGaussian signals. Using the evolutionary spectral approach, we develop methods for evaluating evolutionary bispectrum (time dependent bispectrum) and illustrate the approach with examples. We also define wavelet transforms for discrete parameter time series, and show that higher order moments of these transforms are necessary to study nonlinear signals. The methods are illustrated with examples. Copyright (C) 1996 Published by Elsevier Science Ltd

引用

页码：425 / 452

页数：28

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