Deterministic solutions to QSAT and Q3SAT by spiking neural P systems with pre-computed resources

  • Authors:

  • Tseren-Onolt Ishdorj;Alberto Leporati;Linqiang Pan;Xiangxiang Zeng;Xingyi Zhang

  • Affiliations:

  • Computational Biomodelling Laboratory, Department of Information Technologies, Abo Akademi University, Turku 20520, Finland;Dipartimento di Informatica, Sistemistica e Comunicazione, Università degli Studi di MilanoBicocca, Viale Sarca 336/14, 20126 Milano, Italy;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China;Key Laboratory of Image Processing and Intelligent Control, Department of Control Science and Engineering, Huazhong University of Science and Technology, 430074 Wuhan, China

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2010

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Abstract

In this paper we continue previous studies on the computational efficiency of spiking neural P systems, under the assumption that some pre-computed resources of exponential size are given in advance. Specifically, we give a deterministic solution for each of two well known PSPACE-complete problems: QSAT and Q3SAT. In the case of QSAT, the answer to any instance of the problem is computed in a time which is linear with respect to both the number n of Boolean variables and the number m of clauses that compose the instance. As for Q3SAT, the answer is computed in a time which is at most cubic in the number n of Boolean variables.