Spiking Neural P Systems with Delay on Synapses.

Journal: International journal of neural systems
Published Date:

Abstract

Based on the feature and communication of neurons in animal neural systems, spiking neural P systems (SN P systems) were proposed as a kind of powerful computing model. Considering the length of axons and the information transmission speed on synapses, SN P systems with delay on synapses (SNP-DS systems) are proposed in this work. Unlike the traditional SN P systems, where all the postsynaptic neurons receive spikes at the same instant from their presynaptic neuron, the postsynaptic neurons in SNP-DS systems would receive spikes at different instants, depending on the delay time on the synapses connecting them. It is proved that the SNP-DS systems are universal as number generators. Two small universal SNP-DS systems, with standard or extended rules, are constructed to compute functions, using 56 and 36 neurons, respectively. Moreover, a simulator has been provided, in order to check the correctness of these two SNP-DS systems, thus providing an experimental validation of the universality of the systems designed.

Authors

  • Xiaoxiao Song
    School of Electrical Engineering and Electronic Information, Xihua University, Chengdu 610039, China.
  • Luis Valencia-Cabrera
    Research Group on Natural Computing, Department of Computer Science and Artificial Intelligence, University of Sevilla, Sevilla, Andalucía 41004, Spain.
  • Hong Peng
    1 Center for Radio Administration and Technology Development, School of Computer and Software Engineering, Xihua University, Chengdu 610039, P. R. China.
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
  • Mario J Pérez-Jiménez
    6 Research Group of Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla 41012, Spain.