Solving Subset Sum Problems by Time-free Spiking Neural P Systems

Authors

Tao Song, Key Laboratory of High Performance Ship Technology of Ministry of Education, Wuhan University of Technology, Wuhan, China\\ School of Automation, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China
Liang Luo
Juanjuan He
Zhihua Chen
Kai Zhang

Author Country (or Countries)

China

Abstract

In membrane computing, spiking neural P systems (shortly called SN P systems) are a group of neural-like computing models inspired from the way spiking neurons communication in form of spikes. In previous works, SN P systems working in a nondeterministic manner have been used to solve numerical NP-complete problems, such as SAT, vertex cover, in feasible time. In these works, the application of any rule should complete in exactly one time unit, and the precise execution time of rules plays a crucial role on solving the problems in polynomial (or even in linear) time. However, the restriction does not coincide with the biological fact, since in biological systems, bio-chemical reactions may cost different execution time due to the external uncontrollable conditions. In this paper, we consider timed and time-free SN P systems, where the precise execution time of the rules is removed. To investigate the computational efficiency of time-free SN P systems, we solve Subset Sum problem by a family of uniform time-free SN P systems.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.18576/amis/080140

Recommended Citation

Song, Tao; Luo, Liang; He, Juanjuan; Chen, Zhihua; and Zhang, Kai (2014) "Solving Subset Sum Problems by Time-free Spiking Neural P Systems," Applied Mathematics & Information Sciences: Vol. 08: Iss. 1, Article 40.
DOI: http://dx.doi.org/10.18576/amis/080140
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss1/40