On partial neural-net decoding with retransmissions for data communications

TitleOn partial neural-net decoding with retransmissions for data communications
Publication TypeConference Paper
Year of Publication1991
AuthorsYang, Q., Q. Wang, and V. K. Bhargava
Conference NameWESCANEX '91 'IEEE Western Canada Conference on Computer, Power and Communications Systems in a Rural Environment'
Pagination312 -315
Date Publishedmay.
Keywordsdata communication systems, data communications, decoding, error correction codes, feedforward neural networks, linear block codes, neural nets, neural-net decoder, partial neural-net decoding, pocket algorithm, random sampling algorithm, retransmissions, syndrome decoding methods, throughput performance
Abstract

The authors discuss basic issues on partial decoding of linear block codes with retransmissions by recently developed neural network technology. In particular, the basic structure of a neural-net decoder is defined based on syndrome decoding methods. Partial decoding by the pocket algorithm and the random sampling algorithm is proposed, and its throughput performance is examined. The complexity issues of using feedforward neural networks for decoding programs are also addressed. Neural-net decoding could be a good alternative for providing an error control mechanism for data communications

URLhttp://dx.doi.org/10.1109/WESCAN.1991.160567
DOI10.1109/WESCAN.1991.160567

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