DocumentCode
1191221
Title
Distributed arithmetic perceptron
Author
Martinelli, G. ; Ricotti, L. Prina ; Ragazzini, S.
Author_Institution
INFOCOM, Rome Univ., Italy
Volume
141
Issue
5
fYear
1994
fDate
10/1/1994 12:00:00 AM
Firstpage
382
Lastpage
386
Abstract
The shift of the nonlinearity from the neuron to the input allows the realisation of any mapping by a single perceptron. The resulting perceptron is unimodal and consequently there are no problems of local minima and excessive time-consuming training procedures. In the paper a method is proposed for carrying out this preprocessing in a more general way. Moreover, it is shown that the weights of the connections can be explicitly determined from the training set
Keywords
feedforward neural nets; learning (artificial intelligence); pattern recognition; speech recognition; connection weights; distributed arithmetic perceptron; preprocessing; training set;
fLanguage
English
Journal_Title
Circuits, Devices and Systems, IEE Proceedings -
Publisher
iet
ISSN
1350-2409
Type
jour
DOI
10.1049/ip-cds:19941187
Filename
329869
Link To Document