Title :
A multiple-input OTA circuit for neural networks
Author :
Reed, Russel D. ; Geiger, Randall L.
Author_Institution :
Texas A&M Univ., College Station, TX, USA
fDate :
5/1/1989 12:00:00 AM
Abstract :
An operational transconductance amplifier (OTA) circuit suitable for modeling neurons in VLSI implementations of artificial neural networks (NN) is described. It generates an output voltage which is a sigmoidal-like function of the linear sum of a number of weighted inputs. The weight of each input is individually controlled by a bias voltage which can be varied continuously and dynamically. Large numbers of these cells can be fashioned in regular arrays. It appears to be efficient because each weighted connection is implemented with only two MOSFET transistors
Keywords :
MOS integrated circuits; VLSI; neural nets; operational amplifiers; MOS IC; MOSFET; VLSI; artificial neural networks; modeling neurons; multiple-input OTA circuit; neural networks; operational transconductance amplifier; regular arrays; sigmoidal-like function; weighted inputs; Artificial neural networks; Biological system modeling; Circuits; Neural networks; Neurons; Operational amplifiers; Pattern recognition; Transconductance; Very large scale integration; Voltage control;
Journal_Title :
Circuits and Systems, IEEE Transactions on
