Blind Nonlinear System Identification Under Gaussian And Or IID Excitation Using Genetic Algorithms

被引：0

作者：

Cherif, I. ^{[1
]}

Abid, S. ^{[1
]}

Fnaiech, Farhat ^{[1
]}

机构：

[1] ESSTT, SICISI, Tunis 1008, Tunisia

来源：

ICSPC: 2007 IEEE INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATIONS, VOLS 1-3, PROCEEDINGS | 2007年

关键词：

Blind Identification; Volterra kernels; higher order cumulants; Genetic Algorithm (GA);

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The blind identification of a special class of nonlinear system is pursued in this paper. In particular a genetic algorithm is developed for blind identification of quadratic Volterra model excited by an unobservable input signal which can either be a stationary Gaussian process or an i.i.d process. This approach enables a nonlinear relationship between model kernels and output cumulants up to third order. Simulation results are presented to show good performance of this approach.

引用

页码：644 / 647

页数：4

共 10 条

[1] ANALYSIS AND COMPENSATION OF NONLINEARITIES IN DIGITAL TRANSMISSION-SYSTEMS [J].