Neural networks for modeling nonlinear memoryless communication channels

被引：2

作者：

Ibnkahla, M

Sombrin, J

Castanie, F

Bershad, NJ

机构：

[1] CTR NATL ETUD SPATIALES, F-31055 TOULOUSE, FRANCE

[2] UNIV CALIF IRVINE, DEPT ELECT & COMP ENGN, IRVINE, CA 92717 USA

来源：

IEEE TRANSACTIONS ON COMMUNICATIONS | 1997年 / 45卷 / 07期

关键词：

neural networks; satellite communications; TWT amplifiers;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper presents a neural network approach for modeling nonlinear memoryless communication channels, In particular, the paper studies the approximation of the nonlinear characteristics of traveling-wave tube (TWT) amplifiers used in satellite communications, The modeling is based upon multilayer neural networks, trained by the odd and even backpropagation (BP) algorithms, Simulation results demonstrate that neural network models fit the experimental data better than classical analytical TWT models.

引用

页码：768 / 771

页数：4

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