Solving SAT by parallel execution of neural networks with probabilistic attenuation coefficient generator

Author

Zhang, Kairong ; Nagamatu, Masahiro

Author_Institution

Graduate Sch. of Life Sci. & Syst. Eng., Kyushu Inst. of Technol., Kitakyushu, Japan

Volume

3

fYear

2004

fDate

2-6 Nov. 2004

Firstpage

2163

Abstract

We have proposed a neural network named LPPH for the SAT. In order to solve the SAT more efficiently, a parallel execution has been proposed. Experimental results show that higher ratio of speedup is obtained by using this parallel execution of the LPPH. There is an important parameter named attenuation coefficient in the dynamics of the LPPH, which affects strongly the speed of execution of the LPPH. In this paper, a method is proposed to generate attenuation coefficients for the dynamics of the LPPH by using probabilistic generating function. The experimental results show that this method is efficient.

Keywords

computability; neural nets; parallel processing; execution speed; neural networks; parallel execution; probabilistic attenuation coefficient; satisfiability problem; Application software; Attenuation; Computer science; Decision making; Electronic mail; Lagrangian functions; NP-complete problem; Neural networks; Parallel processing; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE

Print_ISBN

0-7803-8730-9

Type

conf

DOI

10.1109/IECON.2004.1432132

Filename

1432132