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On the computational complexity of spiking neural P systems

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Abstract

It is shown here that there is no standard spiking neural P system that simulates Turing machines with less than exponential time and space overheads. The spiking neural P systems considered here have a constant number of neurons that is independent of the input length. Following this, we construct a universal spiking neural P system with exhaustive use of rules that simulates Turing machines in linear time and has only 10 neurons.

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Notes

  1. In a similar table given in Neary (2010a) the time/space complexity given for a number of the systems is incorrect due to an error copied from Korec’s paper (Korec 1996). For more see the last paragraph of Sect. 3.

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Acknowledgment

The author is funded by Science Foundation Ireland Research Frontiers Programme grant number 07/RFP/CSMFz1.

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Correspondence to Turlough Neary.

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Neary, T. On the computational complexity of spiking neural P systems. Nat Comput 9, 831–851 (2010). https://doi.org/10.1007/s11047-010-9213-1

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  • DOI: https://doi.org/10.1007/s11047-010-9213-1

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