DocumentCode :
3221860
Title :
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
Link To Document :
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