TY - GEN

T1 - Constant-time neural decoders for some BCH codes

AU - Tseng, Yuen Hsien

AU - Wu, Ja Ling

PY - 1994

Y1 - 1994

N2 - High-order neural networks (HONN) are shown to decode some BCH codes in constant-time with very low hardware complexity. HONN is a direct extension of the linear perceptron: it uses a polynomial consisting of a set of product terms as its discriminant function. Because a product term is isomorphic to a parity function and a two-layer perceptron for the parity function has been shown by Rumelhart, Hinton, and Williams (1986), HONN has a simple realization if it is considered as having a set of parity networks in the first-half layer, followed by a linear perceptron in the second-half layer. The main problem in using high-order neural networks for a specific application is to decide a proper set of product terms. We apply genetic algorithms to this structure-adaptation problem.

AB - High-order neural networks (HONN) are shown to decode some BCH codes in constant-time with very low hardware complexity. HONN is a direct extension of the linear perceptron: it uses a polynomial consisting of a set of product terms as its discriminant function. Because a product term is isomorphic to a parity function and a two-layer perceptron for the parity function has been shown by Rumelhart, Hinton, and Williams (1986), HONN has a simple realization if it is considered as having a set of parity networks in the first-half layer, followed by a linear perceptron in the second-half layer. The main problem in using high-order neural networks for a specific application is to decide a proper set of product terms. We apply genetic algorithms to this structure-adaptation problem.

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U2 - 10.1109/ISIT.1994.394675

DO - 10.1109/ISIT.1994.394675

M3 - Conference contribution

AN - SCOPUS:84894379706

SN - 0780320158

SN - 9780780320154

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 343

BT - Proceedings - 1994 IEEE International Symposium on Information Theory, ISIT 1994

T2 - 1994 IEEE International Symposium on Information Theory, ISIT 1994

Y2 - 27 June 1994 through 1 July 1994

ER -