Bridges Between Spiking Neural Membrane Systems and Virus Machines.

Journal: International journal of neural systems
Published Date:

Abstract

Spiking Neural P Systems (SNP) are well-established computing models that take inspiration from spikes between biological neurons; these models have been widely used for both theoretical studies and practical applications. Virus machines (VMs) are an emerging computing paradigm inspired by viral transmission and replication. In this work, a novel extension of VMs inspired by SNPs is presented, called Virus Machines with Host Excitation (VMHEs). In addition, the universality and explicit results between SNPs and VMHEs are compared in both generating and computing mode. The VMHEs defined in this work are shown to be more efficient than SNPs, requiring fewer memory units (hosts in VMHEs and neurons in SNPs) in several tasks, such as a universal machine, which was constructed with 18 hosts less than the 84 neurons in SNPs, and less than other spiking models discussed in the work.

Authors

  • Antonio Ramírez-De-Arellano
    Research Group of Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla 41012, Spain.
  • David Orellana-Martín
    Research Group on Natural Computing, Department of Computer Science and Artificial Intelligence, Universidad de Sevilla, Avenida Reina Mercedes s/n, 41012 Sevilla, Spain.
  • Mario J Pérez-Jiménez
    6 Research Group of Natural Computing, Department of Computer Science and Artificial Intelligence, University of Seville, Sevilla 41012, Spain.