Normal forms for spiking neural P systems

  • Authors:

  • Oscar H. Ibarra;Andrei Pun;Gheorghe Pun;Alfonso Rodríguez-Patón;Petr Sosík;Sara Woodworth

  • Affiliations:

  • Department of Computer Science, University of California, Santa Barbara, CA 93106, USA;Department of Computer Science, Louisiana Tech University, Ruston, PO Box 10348, Louisiana, LA-71272, USA and Universidad Politécnica de Madrid - UPM, Faculdad de Informática, Campus de ...;Institute of Mathematics of the Romanian Academy, PO Box 1-764, 014700 Bucureti, Romania and Department of Computer Science and Artificial Intelligence, University of Sevilla, Avda. Reina Mercedes ...;Universidad Politécnica de Madrid - UPM, Faculdad de Informática, Campus de Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain;Universidad Politécnica de Madrid - UPM, Faculdad de Informática, Campus de Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain and Institute of Computer Science, Silesian Universi ...;Department of Computer Science, University of California, Santa Barbara, CA 93106, USA

  • Venue:
  • Theoretical Computer Science
  • Year:
  • 2007

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Abstract

The spiking neural P systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. In this paper we prove a series of normal forms for spiking neural P systems, concerning the regular expressions used in the firing rules, the delay between firing and spiking, the forgetting rules used, and the outdegree of the graph of synapses. In all cases, surprising simplifications are found, without losing the computational completeness - sometimes at the price of (slightly) increasing other parameters which describe the complexity of these systems.