VLSI design of cellular neural networks with annealing and optical input capabilities

Author

Sheu, Bing J. ; Bang, Sa H. ; Fang, Wai-Chi

Author_Institution

Dept. of Electr. Eng., Univ. of Southern California, Los Angeles, CA, USA

Volume

1

fYear

1995

fDate

30 Apr-3 May 1995

Firstpage

653

Abstract

A cellular neural network (CNN) is a locally connected, massively paralleled computing system with simple synaptic operators so that it is very suitable for VLSI implementation in real-time, high-speed applications. VLSI architecture of a continuous-time shift-invariant CNN with digitally-programmable operators and optical inputs is proposed. Circuits with annealing ability are included to achieve optimal solutions for many selected applications

Keywords

VLSI; cellular neural nets; integrated circuit design; neural chips; VLSI; annealing; cellular neural networks; continuous-time shift-invariant CNN; digitally-programmable operators; high-speed applications; locally connected system; massively paralleled computing system; optical input capabilities; synaptic operators; Annealing; Cellular neural networks; Computer networks; Concurrent computing; High speed optical techniques; Optical computing; Optical design; Optical fiber networks; Real time systems; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-2570-2

Type

conf

DOI

10.1109/ISCAS.1995.521598

Filename

521598