Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes
Abstract
\Ve present. an approach for df'velopment of a decoder for any complex binary error-correct.ing code- (ECC) via training from examples of decoded received words. Our decoder is a connectionist architecture. We describe two sepa.rate solutions: A system-level solution (the Cascaded Networks Decoder); and the ECC-Enhanced Decoder, a solution which simplifies the mapping problem which must be solved for decoding. Although both solutions meet our basic approach constraint for simplicity and compact(cid:173) ness. only the ECC-Enhanced Decoder meet.s our second basic constraint of being a generic solution.
Cite
Text
Gish and Blaum. "Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes." Neural Information Processing Systems, 1991.Markdown
[Gish and Blaum. "Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes." Neural Information Processing Systems, 1991.](https://mlanthology.org/neurips/1991/gish1991neurips-adaptive/)BibTeX
@inproceedings{gish1991neurips-adaptive,
title = {{Adaptive Development of Connectionist Decoders for Complex Error-Correcting Codes}},
author = {Gish, Sheri L. and Blaum, Mario},
booktitle = {Neural Information Processing Systems},
year = {1991},
pages = {691-697},
url = {https://mlanthology.org/neurips/1991/gish1991neurips-adaptive/}
}