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Simple adaptive momentum: new algorithm for training multilayer perceptrons

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Swanston, D. J., Bishop, J. M. and Mitchell, R. J. (1994) Simple adaptive momentum: new algorithm for training multilayer perceptrons. Electronics Letters, 30 (18). pp. 1498-1500. ISSN 0013-5194 doi: 10.1049/el:19941014

Abstract/Summary

The speed of convergence while training is an important consideration in the use of neural nets. The authors outline a new training algorithm which reduces both the number of iterations and training time required for convergence of multilayer perceptrons, compared to standard back-propagation and conjugate gradient descent algorithms.

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Item Type Article
URI https://reading-clone.eprints-hosting.org/id/eprint/18869
Identification Number/DOI 10.1049/el:19941014
Refereed Yes
Divisions Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
Uncontrolled Keywords adaptive momentum, iterations, multilayer perceptrons, neural nets, speed of convergence, training algorithm, training time
Publisher Institution of Engineering and Technology (IET)
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