Accessibility navigation


Simple adaptive momentum: new algorithm for training multilayer perceptrons

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

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item 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.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Mathematical, Physical and Computational Sciences > Department of Computer Science
ID Code:18869
Uncontrolled Keywords:adaptive momentum, iterations, multilayer perceptrons, neural nets, speed of convergence, training algorithm, training time
Publisher:Institution of Engineering and Technology (IET)

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation