Adaptive quadratic Neural Nets.

S.G. Lim; Michael Alder; P.T. Hadingham

doi:10.1016/0167-8655(92)90029-Y

Adaptive quadratic Neural Nets.

S.G. Lim, Michael Alder, P.T. Hadingham

School of Molecular Sciences

Research output: Contribution to journal › Article

8 Citations (Scopus)

Abstract

We present the theory and some results of a new algorithm for Artificial Neural Nets which behaves well on complex data sets. The algorithm uses adaptive quadratic forms as discriminant functions and is very fast compared with Back-Propagation - improvements of four orders of magnitude have been obtained.

Original language	English
Pages (from-to)	325-329
Journal	Pattern Recognition Letters
Volume	13
Issue number	May, 1992
DOIs	https://doi.org/10.1016/0167-8655(92)90029-Y
Publication status	Published - 1992

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title = "Adaptive quadratic Neural Nets.",

abstract = "We present the theory and some results of a new algorithm for Artificial Neural Nets which behaves well on complex data sets. The algorithm uses adaptive quadratic forms as discriminant functions and is very fast compared with Back-Propagation - improvements of four orders of magnitude have been obtained.",

author = "S.G. Lim and Michael Alder and P.T. Hadingham",

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AU - Alder, Michael

AU - Hadingham, P.T.

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AB - We present the theory and some results of a new algorithm for Artificial Neural Nets which behaves well on complex data sets. The algorithm uses adaptive quadratic forms as discriminant functions and is very fast compared with Back-Propagation - improvements of four orders of magnitude have been obtained.

U2 - 10.1016/0167-8655(92)90029-Y

DO - 10.1016/0167-8655(92)90029-Y

M3 - Article

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SP - 325

EP - 329

JO - Pattern Recogniton Letters

JF - Pattern Recogniton Letters

SN - 0167-8655

IS - May, 1992

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