Title :
Applying Hopfield network to find the minimum cost coverage of a Boolean function
Author_Institution :
Dept. of Electr. Eng., Cleveland State Univ., OH, USA
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;
Conference_Titel :
VLSI, 1991. Proceedings., First Great Lakes Symposium on
Conference_Location :
Kalamazoo, MI
Print_ISBN :
0-8186-2170-2
DOI :
10.1109/GLSV.1991.143963