DocumentCode
2045477
Title
A neural network approach to circuit extraction
Author
Zhang, Q.J. ; Wang, F.
Author_Institution
Dept. of Electron., Carleton Univ., Ottawa, Ont., Canada
Volume
1
fYear
1996
fDate
18-21 Aug 1996
Firstpage
475
Abstract
A new application problem, i.e., circuit extraction, for neural networks is developed in this paper. A new formulation to represent the circuit extraction problem by numerical pattern recognition is proposed. Multilayer perceptrons (MLP) are utilized to learn the circuit information and to use this knowledge to extract the circuit macromodels
Keywords
VLSI; circuit CAD; integrated circuit design; integrated circuit modelling; logic design; multilayer perceptrons; pattern recognition; reverse engineering; VLSI design; circuit extraction; circuit macromodels; logic circuits; multilayer perceptrons; neural network approach; numerical pattern recognition; Circuit testing; Consumer electronics; Data mining; Documentation; Expert systems; Multilayer perceptrons; Neural networks; Pattern recognition; Time to market; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1996., IEEE 39th Midwest symposium on
Conference_Location
Ames, IA
Print_ISBN
0-7803-3636-4
Type
conf
DOI
10.1109/MWSCAS.1996.594204
Filename
594204
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