Using a semi-asynchronous Hopfield network to obtain optimal coverage in logic minimization

Author

Chu, Pong P.

Author_Institution

Dept. of Electr. Eng., Cleveland State Univ., OH, USA

Volume

i

fYear

1991

fDate

8-14 Jul 1991

Firstpage

141

Abstract

Applies the neural network approach to solve the minimal coverage problem. The procedure to obtain the minimal expression of a Boolean function includes a step to find a cover with minimal cost. Since this step is an NP-complete problem, it is impractical to find an optimal solution for a large data size. The neural network approach is used to solve this problem. The authors first formulate this problem, and then define an energy function and map it to a modified Hopfield network, which includes a layer of regular neurons and a layer of synchronous neurons. The formulation and construction of the network are discussed

Keywords

Boolean functions; computational complexity; logic CAD; minimisation of switching nets; neural nets; Boolean function; NP-complete problem; energy function; logic minimization; minimal cost; minimal coverage; neural network; semi-asynchronous Hopfield network; synchronous neurons; Boolean functions; Computer networks; Cost function; Intelligent networks; Logic; Minimization; NP-complete problem; Neural networks; Neurons; Traveling salesman problems;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on

Conference_Location

Seattle, WA

Print_ISBN

0-7803-0164-1

Type

conf

DOI

10.1109/IJCNN.1991.155165

Filename

155165