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

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

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

Bing J. Sheu^*
, Sa H. Bang
, Wai Chi Fang

^*Corresponding author for this work

University of Southern California

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

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. The circuits with annealing ability is included to achieve optimal solutions for many selected applications.

Original language	English
Pages (from-to)	653-659
Number of pages	7
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
Volume	1
State	Published - 1995
Externally published	Yes
Event	Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) - Seattle, WA, USA Duration: 30 04 1995 → 03 05 1995

Cite this

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title = "VLSI design of cellular neural networks with annealing and optical input capabilities",

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. The circuits with annealing ability is included to achieve optimal solutions for many selected applications.",

author = "Sheu, \{Bing J.\} and Bang, \{Sa H.\} and Fang, \{Wai Chi\}",

year = "1995",

language = "英语",

volume = "1",

pages = "653--659",

journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

issn = "0271-4310",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3) ; Conference date: 30-04-1995 Through 03-05-1995",

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T1 - VLSI design of cellular neural networks with annealing and optical input capabilities

AU - Sheu, Bing J.

AU - Bang, Sa H.

AU - Fang, Wai Chi

PY - 1995

Y1 - 1995

N2 - 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. The circuits with annealing ability is included to achieve optimal solutions for many selected applications.

AB - 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. The circuits with annealing ability is included to achieve optimal solutions for many selected applications.

UR - https://www.scopus.com/pages/publications/0029192792

M3 - 会议文章

AN - SCOPUS:0029192792

SN - 0271-4310

VL - 1

SP - 653

EP - 659

JO - Proceedings - IEEE International Symposium on Circuits and Systems

JF - Proceedings - IEEE International Symposium on Circuits and Systems

T2 - Proceedings of the 1995 IEEE International Symposium on Circuits and Systems-ISCAS 95. Part 3 (of 3)

Y2 - 30 April 1995 through 3 May 1995

ER -

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

Abstract

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