DocumentCode :
2615056
Title :
A neural processing node with on-chip learning
Author :
Donald, James ; Akers, Lex A.
Author_Institution :
Center for Solid State Electron. Res., Arizona State Univ., Tempe, AZ, USA
fYear :
1993
fDate :
3-6 May 1993
Firstpage :
2748
Abstract :
Real-time control requires adaptive, analog VLSI chips. The authors describe the design and test results of an adaptive analog processing chip. These chips are pulse coded signals for communication between processing nodes and analog weights for information storage. The adaptive rule is implemented on chip. Experimental results demonstrate that the network produces unsupervised linearly separable outputs that correspond to dominant features of the inputs
Keywords :
VLSI; adaptive signal processing; analogue processing circuits; neural chips; pulse code modulation; adaptive analog processing chip; analog VLSI chips; dominant features; neural processing node; on-chip learning; processing nodes; pulse coded signals; unsupervised linearly separable outputs; Adaptive control; Communication system control; Control systems; Negative feedback; Neural networks; Neurons; Programmable control; Statistics; Threshold voltage; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
Type :
conf
DOI :
10.1109/ISCAS.1993.394336
Filename :
394336
Link To Document :
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