Dense CMOS design of cellular neural networks with programmable synaptic weights

Sa H. Bang; Bing J. Sheu

Dense CMOS design of cellular neural networks with programmable synaptic weights

Sa H. Bang^*
, Bing J. Sheu

^*Corresponding author for this work

University of Southern California

Research output: Contribution to conference › Conference Paper › peer-review

Abstract

Design of a continuous-time, shift-invariant CNN with digitally-programmable synaptic operators is described. In addition, the hardware annealing capability is included to provide the maximum flexibility over a variety of applications such as image processing, unconstrained optimization, and generalized analog computing framework. The simulation results are also presented.

Original language	English
Pages	1923-1928
Number of pages	6
State	Published - 1994
Externally published	Yes
Event	Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) - Orlando, FL, USA Duration: 27 06 1994 → 29 06 1994

Conference

Conference	Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
City	Orlando, FL, USA
Period	27/06/94 → 29/06/94

Cite this

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title = "Dense CMOS design of cellular neural networks with programmable synaptic weights",

abstract = "Design of a continuous-time, shift-invariant CNN with digitally-programmable synaptic operators is described. In addition, the hardware annealing capability is included to provide the maximum flexibility over a variety of applications such as image processing, unconstrained optimization, and generalized analog computing framework. The simulation results are also presented.",

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

year = "1994",

language = "英语",

pages = "1923--1928",

note = "Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7) ; Conference date: 27-06-1994 Through 29-06-1994",

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AU - Bang, Sa H.

AU - Sheu, Bing J.

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AB - Design of a continuous-time, shift-invariant CNN with digitally-programmable synaptic operators is described. In addition, the hardware annealing capability is included to provide the maximum flexibility over a variety of applications such as image processing, unconstrained optimization, and generalized analog computing framework. The simulation results are also presented.

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M3 - 论文

AN - SCOPUS:0028748428

SP - 1923

EP - 1928

T2 - Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)

Y2 - 27 June 1994 through 29 June 1994

ER -

Dense CMOS design of cellular neural networks with programmable synaptic weights

Abstract

Conference

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