Spiking neural P systems with neuron division

  • Authors:

  • Jun Wang;Hendrik Jan Hoogeboom;Linqiang Pan

  • Affiliations:

  • Image Processing and Int. Control Key Lab. of Education Ministry, Dept. of Control Science and Eng., Huazhong Univ. of Science and Technology, Hubei, China and Leiden Institute of Advanced Compute ...;Leiden Institute of Advanced Computer Science, Universiteit Leiden, Leiden, The Netherlands;Image Processing and Intelligent Control Key Laboratory of Education Ministry, Department of Control Science and Engineering, Huazhong University of Science and Technology, Hubei, China

  • Venue:
  • CMC'10 Proceedings of the 11th international conference on Membrane computing
  • Year:
  • 2010

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Abstract

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. The features of neuron division and neuron budding are recently introduced into the framework of SN P systems, and it was shown that SN P systems with neuron division and neuron budding can efficiently solve computationally hard problems. In this work, the computation power of SN P systems with neuron division only, without budding, is investigated; it is proved that a uniform family of SN P systems with neuron division can efficiently solve SAT in a deterministic way, not using budding, while additionally limiting the initial size of the system to a constant number of neurons. This answers an open problem formulated by Pan et al.