A neural network communication equalizer with optimized solution capability

Author

Chen, David C. ; Sheu, Bing J. ; Chou, Eric Y.

Author_Institution

Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA

Volume

4

fYear

1996

fDate

3-6 Jun 1996

Firstpage

1957

Abstract

Artificial neural network approaches in communication have been motivated by the adaptive learning capability and the collective computational properties to process real world signals. In this paper, a one-dimensional compact neural network receiver as a paralleled computational framework of the maximum likelihood sequence estimation (MLSE) is presented. Optimum solution can be obtained by applying the hardware annealing which is a deterministic method for searching a globally minimum energy state in a short period of time

Keywords

Gaussian noise; digital communication; equalisers; intersymbol interference; maximum likelihood estimation; neural nets; signal processing; simulated annealing; adaptive learning capability; deterministic method; globally minimum energy state; hardware annealing; maximum likelihood sequence estimation; neural network communication equalizer; one-dimensional compact neural network receiver; optimized solution capability; paralleled computational framework; Annealing; Artificial neural networks; Computer networks; Concurrent computing; Energy states; Equalizers; Hardware; Maximum likelihood estimation; Neural networks; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1996., IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

0-7803-3210-5

Type

conf

DOI

10.1109/ICNN.1996.549201

Filename

549201