DocumentCode :
1117168
Title :
An associative memory based on an electronic neural network architecture
Author :
Howard, Richard E. ; Schwartz, Daniel B. ; Denker, J.S. ; Epworth, Roger W. ; Graf, H.P. ; Hubbard, Wayne E. ; Jackel, Lawrence D. ; Straughn, Brian L. ; Tennant, D.M.
Author_Institution :
AT&T Bell Laboratories, Holmdel, NJ
Volume :
34
Issue :
7
fYear :
1987
fDate :
7/1/1987 12:00:00 AM
Firstpage :
1553
Lastpage :
1556
Abstract :
A high-density matrix of α-Si resistors was made to demonstrate a new type of parallel-processing associative memory consisting of an interconnected array of analog amplifiers. The 22 × 22 resistor matrix was made using a technology compatible with conventional VLSI processing. This demonstration circuit can recall up to four 22- bit memories in 1 to 10 µs while correcting errors in the input word of at least 5 bits. This function is difficult to perform efficiently in conventional digital hardware and is the basis for solving a variety of pattern-recognition problems including vision and speech.
Keywords :
Associative memory; Biological neural networks; Hardware; Integrated circuit interconnections; Neural networks; Pattern recognition; Resistors; Symmetric matrices; Transfer functions; Voltage;
fLanguage :
English
Journal_Title :
Electron Devices, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9383
Type :
jour
DOI :
10.1109/T-ED.1987.23118
Filename :
1486829
Link To Document :
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