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Characterizations of some classes of spiking neural P systems

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Abstract

We look at the recently introduced neural-like systems, called SN P systems. These systems incorporate the ideas of spiking neurons into membrane computing. We study various classes and characterize their computing power and complexity. In particular, we analyze asynchronous and sequential SN P systems and present some conditions under which they become (non-)universal. The non-universal variants are characterized by monotonic counter machines and partially blind counter machines and, hence, have many decidable properties. We also investigate the language-generating capability of SN P systems.

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Acknowledgements

This research was supported in part by NSF Grants CCF-0430945 and CCF-0524136.

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Authors and Affiliations

  1. Department of Computer Science, University of California, Santa Barbara, CA, 93106, USA

    Oscar H. Ibarra & Sara Woodworth

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  1. Oscar H. Ibarra
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  2. Sara Woodworth
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Correspondence to Oscar H. Ibarra.

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Ibarra, O.H., Woodworth, S. Characterizations of some classes of spiking neural P systems. Nat Comput 7, 499–517 (2008). https://doi.org/10.1007/s11047-008-9084-x

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