DocumentCode
2662444
Title
Analog VLSI implementation of neural networks
Author
Vittoz, Eric A.
Author_Institution
Swiss Center for Electron. & Microtechnol., Neuchatel, Switzerland
fYear
1990
fDate
1-3 May 1990
Firstpage
2524
Abstract
The potentialities of CMOS analog VLSI for the implementation of neural systems are demonstrated. It is shown how the various modes of operation of the transistor can be exploited to build very efficient neurons on a very small area with very low power consumption. The connectivity problem can be alleviated by selecting appropriate architectures. Various methods for implementing analog synaptic memories are discussed, and examples of working chips are given
Keywords
CMOS integrated circuits; VLSI; neural nets; analog CMOS ICs; analog VLSI implementation; analog synaptic memories; connectivity problem; efficient neurons; examples of working chips; low power consumption; modes of operation; neural networks; small area; Biology computing; CMOS technology; MOSFETs; Neural networks; Neurons; Parallel processing; Threshold voltage; Transconductance; Very large scale integration; Voltage control;
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.1990.112524
Filename
112524
Link To Document