DocumentCode :
899825
Title :
Distributed arithmetic implementation of artificial neural networks
Author :
Bochev, Vladimir
Author_Institution :
Bulgarian Acad. of Sci., Sofia, Bulgaria
Volume :
41
Issue :
5
fYear :
1993
fDate :
5/1/1993 12:00:00 AM
Firstpage :
2010
Lastpage :
2013
Abstract :
A brief overview of the computational requirements and some hardware developments for backpropagation networks is presented. The basic distributed arithmetic approach as it is used in digital filter implementations is discussed. A hardware neural network, the design of which is based on distributed arithmetic, is described. The proposed formal neuron has a regular circuit pattern as it consists mostly of memory hardware. Thus a wafer scale implementation of a network composed of such neurons may provide a cost effective way to solve many real-time pattern recognition problems
Keywords :
backpropagation; digital arithmetic; neural chips; pattern recognition; artificial neural networks; backpropagation networks; distributed arithmetic approach; real-time pattern recognition problems; wafer scale implementation; Artificial neural networks; Backpropagation; Circuits; Computer networks; Costs; Digital arithmetic; Digital filters; Neural network hardware; Neurons; Pattern recognition;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.215327
Filename :
215327
Link To Document :
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