Digital satellite channel identification using neural networks: analytic models

Author

Bershad, N.J. ; Ibnkhala, M. ; Castanie, F.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Irvine, CA, USA

fYear

1997

fDate

16-18 April 1997

Firstpage

317

Lastpage

320

Abstract

This paper studies the statistical transient and convergence behavior of a neural network structure (filter-nonlinearity-filter) that adapts its parameters using a modified version of the backpropagation algorithm. A previous paper has used this structure to model and identify nonlinear satellite channels with memory. This paper derives simplified analytical models which qualitatively predict the algorithm behavior observed previously.

Keywords

adaptive estimation; backpropagation; convergence of numerical methods; digital communication; filtering theory; identification; neural nets; satellite communication; statistical analysis; telecommunication channels; analytic models; backpropagation algorithm; digital satellite channel identification; filter-nonlinearity-filter; memory; neural networks; nonlinear satellite channels; statistical convergence behavior; statistical transient behavior; Adaptive filters; Backpropagation algorithms; Convergence; Delay effects; Neural networks; Nonlinear filters; Predictive models; Satellites; Signal processing algorithms; Transversal filters;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing Advances in Wireless Communications, First IEEE Signal Processing Workshop on

Conference_Location

Paris, France

Print_ISBN

0-7803-3944-4

Type

conf

DOI

10.1109/SPAWC.1997.630378

Filename

630378