Online tracking of the degree of nonlinearity within complex signals

被引：5

作者：

Mandic, Danilo P. ^{[1
]}

Vayanos, Phebe ^{[1
]}

Javidi, Soroush ^{[1
]}

Jelfs, Beth ^{[1
]}

Aihara, Kazuyuki ^{[2
]}

机构：

[1] Univ London Imperial Coll Sci Technol & Med, London SW7 2AZ, England

[2] Univ Tokyo, Tokyo 1138654, Japan

来源：

2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12 | 2008年

关键词：

adaptive signal processing; complex LMS; convex optimisation; machine learning; wind modelling;

D O I：

10.1109/ICASSP.2008.4518046

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

A novel method for online tracking of the changes in the nonlinearity within complex-valued signals is introduced. This is achieved by a collaborative adaptive signal processing approach by means of a hybrid filter. By tracking the dynamics of the adaptive mixing parameter within the employed hybrid filtering architecture, we show that it is possible to quantify the degree of nonlinearity within complex-valued data. Simulations on both benchmark and real world data support the approach.

引用

页码：2061 / +

页数：3

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