A feedforward neural network for CMOS VLSI implementation

Author

Salam, Fathi M A ; Choi, Myung-Ryul

Author_Institution

Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA

fYear

1989

fDate

14-16 Aug 1989

Firstpage

489

Abstract

A feedforward neural network circuit model suitable for CMOS VLSI implementation is introduced. The model captures the principles of operation of artificial neural nets, and is suitable for analog all-MOS VLSI circuit implementations. Each unit consists of a control device and one operational amplifier which is implemented with two CMOS inverters in series. A control device is implemented with one n-MOS and one p-MOS transistors to model biasing. A single n-MOS transistor is used to connect the output of a unit of one layer to the input of the next layer. All the connection weights are set by applying analog signals to the gates of these transistors

Keywords

CMOS integrated circuits; VLSI; analogue computer circuits; network synthesis; neural nets; semiconductor device models; CMOS VLSI implementation; CMOS inverters; analogue IC; artificial neural nets; circuit model; connection weights; feedforward neural network; model biasing; operational amplifier; Artificial neural networks; Circuits; Feedforward neural networks; Neural networks; Neurofeedback; Neurons; Semiconductor device modeling; Silicon; Very large scale integration; Voltage;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1989., Proceedings of the 32nd Midwest Symposium on

Conference_Location

Champaign, IL

Type

conf

DOI

10.1109/MWSCAS.1989.101898

Filename

101898