DocumentCode
1875288
Title
A multi-chip module implementation of a neural network
Author
Stout, Matthew G. ; Salmo, Linton G. ; Rudolph, George L. ; Martinez, Tony R.
Author_Institution
Dept. of Electr. & Comput. Eng., Brigham Young Univ., Provo, UT, USA
fYear
1994
fDate
15-17 Mar 1994
Firstpage
20
Lastpage
25
Abstract
The requirement for dense interconnect in artificial neural network systems has led researchers to seek high-density interconnect technologies. This paper reports an implementation using multi-chip modules (MCMs) as the interconnect medium. The specific system described is a self-organizing, parallel, and dynamic learning model which requires a dense interconnect technology for effective implementation; this requirement is fulfilled by exploiting MCM technology. The ideas presented in this paper regarding an MCM implementation of artificial neural networks are versatile and can be adapted to apply to other neural network and connectionist models
Keywords
learning (artificial intelligence); multichip modules; neural chips; parallel architectures; self-organising feature maps; MCM technology; artificial neural network; connectionist models; high-density interconnect technologies; multi-chip module implementation; parallel architecture; self-organizing parallel dynamic learning model; Artificial neural networks; Computational modeling; Computer networks; Computer simulation; Equations; Neural network hardware; Neural networks; Neurons; Parallel architectures; Pattern recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Multi-Chip Module Conference, 1994. MCMC-94, Proceedings., 1994 IEEE
Conference_Location
Santa Cruz, CA
Print_ISBN
0-8186-5560-7
Type
conf
DOI
10.1109/MCMC.1994.292532
Filename
292532
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