Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Sequential SNP systems based on min/max spike numbers
Year:2009
Research Areas
  • Artificial intelligence
Information
Abstract
We consider the properties of spiking neural P (SNP) systems that work in a sequential manner. These SNP systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. The general sequentiality of these systems was considered previously; now we focus on the sequentiality induced by the spike number: at each step, the neuron with the maximum (or minimum) number of spikes among the neurons that are active (can spike) will fire. This strategy corresponds to a global view of the whole network that makes the system sequential. We study the properties of this type of a restriction (i.e. considering the case of sequentiality induced by the function maximum defined on numbers of spikes as well as the case of the sequentiality induced by the function minimum similarly defined on numbers of spikes). Several universality results are obtained for the cases of maximum and minimum induced sequentiality.
International
Si
JCR
Si
Title
THEORETICAL COMPUTER SCIENCE
ISBN
0304-3975
Impact factor JCR
0,806
Impact info
Volume
410
http://dx.doi.org/10.1016/j.tcs.2009.03.004
Journal number
30
From page
2982
To page
2991
Month
AGOSTO
Ranking
Participants
  • Participante: Oscar H Ibarra (Department of Computer Science, University of California, Santa Barbara, CA 93106, USA)
  • Autor: Paul Andrei Paun (UPM)
  • Autor: Alfonso Vicente Rodriguez-Paton Aradas (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial
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