Selection of the most “efficient” Reed-Solomon code for a specific application using neural networks

Author

Benjamin, Henderson ; Kamali, Behnam

Author_Institution

Dept. of Electr. & Comput. Eng., Mercer Univ., GA, USA

fYear

1999

fDate

6-10 Jun 1999

Firstpage

58

Lastpage

61

Abstract

Reed-Solomon (RS) codes have found a widespread applications in digital communications and digital recording systems in the past two decades. The catalog of Reed-Solomon is a rather long one. To select a proper code for a given application, the system designer is compelled to deal with numerous tables, graphs and equations. We introduce a novel application of artificial neural networks (NN) in selecting the most “efficient” RS code for a specific design scenario. It is shown that 98.04% of the time the NN makes correct selections

Keywords

Reed-Solomon codes; digital communication; digital storage; multilayer perceptrons; ANN training; RS code; artificial neural networks; digital communications systems; digital recording systems; digital storage; efficient Reed-Solomon code; multilayered neural network; Application software; Artificial intelligence; Artificial neural networks; Computer networks; Digital communication; Equations; Error correction codes; Humans; Neural networks; Reed-Solomon codes;

fLanguage

English

Publisher

ieee

Conference_Titel

Communication Theory Mini-Conference, 1999

Conference_Location

Vancouver, BC

Print_ISBN

0-7803-5653-5

Type

conf

DOI

10.1109/CTMC.1999.790237

Filename

790237