Proceedings of the Annual Conference of Biomedical Fuzzy Systems Association
Online ISSN : 2424-2586
Print ISSN : 1345-1510
ISSN-L : 1345-1510
13
Conference information

Speedup Solving SAT by Adding New Clauses for Lagrange Programing Neural Network
Shuji IwamiMasahiro Nagamatsu
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Pages 26-29

Details
Abstract
Satisfiability problem (SAT) of the prepositional calculus is a problem to find a variable assignment which satisfies the given Boolean expression in conjunctive normal form (CNF). The SAT is one of the most fundamental and important problems in the field of information science. We proposed a neural network called LPPH (Lagrange Programming neural network with Polarized High-order connections) for solving the SAT. We also proposed several improvement for the LPPH , such as LPPH with attenuation coefficient and double weighted LPPH. In this paper we propose a method to add new clause to the given CNF to speedup the LPPH.
Content from these authors
© 2000 Biomedical Fuzzy Systems Association
Previous article Next article
feedback
Top