DocumentCode :
285793
Title :
Competitive learning in asynchronous pulse density integrated circuits
Author :
Watola, David ; Gembala, David ; Meador, Jack
Author_Institution :
Sch. of Electr. Eng. & Comput. Sci., Washington State Univ., Pullman, WA, USA
Volume :
5
fYear :
1992
fDate :
10-13 May 1992
Firstpage :
2216
Abstract :
The authors introduce a MOS circuit for the integrated implementation of pulse-coded competitive learning. They describe an autoadaptive synapse circuit for a pulse-coded competitive learning rule. The specific focus is upon an adaptive synapse cell which combines a capacitive analog storage element with subthreshold adaptation circuitry. The adaptation circuitry is designed to compensate for nonlinear device transconductance in the subthreshold operating region. The simulation results presented verify circuit operation in a 2-input-3-output competitive network. Accurate clustering of random training data was demonstrated
Keywords :
Hebbian learning; MOS integrated circuits; learning (artificial intelligence); neural chips; pulse-code modulation; 2-input-3-output competitive network; Hebbian adaptation rule; MOS circuit; adaptive synapse cell; asynchronous pulse density integrated circuits; autoadaptive synapse circuit; capacitive analog storage element; nonlinear device transconductance compensation; pulse-coded competitive learning; random training data clustering; simulation; subthreshold adaptation circuitry; Circuit simulation; Computer science; Convergence; Lifting equipment; Neurons; Prototypes; Pulse circuits; Pulse measurements; Training data; Transconductance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1992. ISCAS '92. Proceedings., 1992 IEEE International Symposium on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-0593-0
Type :
conf
DOI :
10.1109/ISCAS.1992.230550
Filename :
230550
Link To Document :
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