Analog neural network building blocks based on current mode subthreshold operation

Author

Song, L. ; Elmasry, M.I. ; Vannelli, A.

Author_Institution

Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada

fYear

1993

fDate

3-6 May 1993

Firstpage

2462

Abstract

A class of analog circuit building blocks for neural network implementation is presented which is based on the current mode subthreshold operation. This class of circuits includes current inverter, current-current multiplier, current amplifier and current comparator. A feedforward network with learning constructed by these building blocks was verified. These building blocks can be applied to artificial neural network (ANN) design in particular and to analog signal processing in general

Keywords

analogue multipliers; analogue processing circuits; comparators (circuits); feedforward neural nets; invertors; learning (artificial intelligence); analog circuit building blocks; analog signal processing; artificial neural network; current amplifier; current comparator; current inverter; current mode subthreshold operation; current-current multiplier; feedforward network; learning; neural network implementation; Analog circuits; Artificial neural networks; Inverters; MOSFETs; Neural networks; Neurons; Power dissipation; Signal design; Signal processing; Voltage;

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.1993.394263

Filename

394263