DocumentCode :
2616866
Title :
New artificial neural net models: basic theory and characteristics
Author :
Salam, Fathi M A
Author_Institution :
Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA
fYear :
1990
fDate :
1-3 May 1990
Firstpage :
200
Abstract :
Models for feedback artificial neural nets (ANNs) which are shown to have qualitatively the same dynamic properties as gradient continuous-time feedback neural nets are presented. These models are based on biological neural nets where neurons have dendrodendritic connections i.e. where connections among neurons occur via dendrites only. These models have the maximum number of connections equal to n (n+1)/2, where n is the number of neurons. The synaptic weights are naturally symmetric. One model uses nonlinear weights are naturally symmetric. One model uses nonlinear floating MOSFET transistors for its dendritic connection, where its conductance is controlled via the gate voltage. This last model lends itself naturally to analog all-MOS VLSI implementation
Keywords :
MOS integrated circuits; VLSI; analogue circuits; insulated gate field effect transistors; neural nets; analog all-MOS VLSI implementation; artificial neural net models; biological neural nets; conductance; dendrodendritic connections; dynamic properties; feedback artificial neural nets; gate voltage; neurons; nonlinear floating MOSFET; nonlinear weights; synaptic weights; Artificial neural networks; Biological system modeling; Feedback circuits; Hardware; Joining processes; MOSFET circuits; Neurofeedback; Neurons; State feedback; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
Type :
conf
DOI :
10.1109/ISCAS.1990.111968
Filename :
111968
Link To Document :
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