Neural network error correcting decoders for block and convolutional codes

Author

Caid, William R. ; Means, Robert W.

fYear

1990

fDate

2-5 Dec 1990

Firstpage

1028

Abstract

The use of neural networks as error correcting decoders is described. It is shown that the neural networks may offer advantages in electronic countermeasure (ECM) environments in which the convolutional design assumptions of additive white Gaussian noise (AWGN) and a binary symmetric channel (BSC) are violated. Some results of preliminary studies and benefits of the neural-based decoder approach are discussed

Keywords

decoding; electronic countermeasures; error correction; neural nets; AWGN; ECM environments; additive white Gaussian noise; binary symmetric channel; block codes; convolutional codes; convolutional design; electronic countermeasure; error correcting decoders; neural networks; neural-based decoder; AWGN; Additive white noise; Character generation; Computational modeling; Convolutional codes; Decoding; Electrochemical machining; Error correction codes; Jamming; Neural networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Global Telecommunications Conference, 1990, and Exhibition. 'Communications: Connecting the Future', GLOBECOM '90., IEEE

Conference_Location

San Diego, CA

Print_ISBN

0-87942-632-2

Type

conf

DOI

10.1109/GLOCOM.1990.116658

Filename

116658

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2963904