DocumentCode :
3335346
Title :
Applying Hopfield network to find the minimum cost coverage of a Boolean function
Author :
Chu, Pong P.
Author_Institution :
Dept. of Electr. Eng., Cleveland State Univ., OH, USA
fYear :
1991
fDate :
1-2 Mar 1991
Firstpage :
182
Lastpage :
185
Abstract :
To find a minimal expression of a Boolean function includes a step to select the minimum cost cover from a set of implicants. Since the selection process is an NP-complete problem, to find an optimal solution is impractical for large input data size. In this paper, the author tries to apply neural network approach to solve this problem. He first formulates this problem and then defines an `energy function´ and maps it to a modified Hopfield network, which will automatically search for minima
Keywords :
Boolean functions; computational complexity; minimisation of switching nets; neural nets; Boolean function; Hopfield network; NP-complete problem; logic minimisation; minimum cost coverage; Artificial neural networks; Boolean functions; Computer networks; Cost function; Energy states; Information processing; Minimization methods; NP-complete problem; Neural networks; Neurons;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
VLSI, 1991. Proceedings., First Great Lakes Symposium on
Conference_Location :
Kalamazoo, MI
Print_ISBN :
0-8186-2170-2
Type :
conf
DOI :
10.1109/GLSV.1991.143963
Filename :
143963
Link To Document :
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