Adaptive quadratic Neural Nets.

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

Research output: Contribution to journalArticle

9 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 languageEnglish
Pages (from-to)325-329
JournalPattern Recognition Letters
Volume13
Issue numberMay, 1992
DOIs
Publication statusPublished - 1992

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Neural networks
Backpropagation

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Lim, S. G., Alder, M., & Hadingham, P. T. (1992). Adaptive quadratic Neural Nets. Pattern Recognition Letters, 13(May, 1992), 325-329. https://doi.org/10.1016/0167-8655(92)90029-Y
Lim, S.G. ; Alder, Michael ; Hadingham, P.T. / Adaptive quadratic Neural Nets. In: Pattern Recognition Letters. 1992 ; Vol. 13, No. May, 1992. pp. 325-329.
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Lim, SG, Alder, M & Hadingham, PT 1992, 'Adaptive quadratic Neural Nets.' Pattern Recognition Letters, vol. 13, no. May, 1992, pp. 325-329. https://doi.org/10.1016/0167-8655(92)90029-Y

Adaptive quadratic Neural Nets. / Lim, S.G.; Alder, Michael; Hadingham, P.T.

In: Pattern Recognition Letters, Vol. 13, No. May, 1992, 1992, p. 325-329.

Research output: Contribution to journalArticle

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AU - Lim, S.G.

AU - Alder, Michael

AU - Hadingham, P.T.

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