Observatorio de I+D+i UPM

Memorias de investigación
Research Publications in journals:
Spiking Neural P systems with Scheduled Synapses
Year:2017
Research Areas
  • Artificial intelligence (neuronal nets, expert systems, etc),
  • Computational biology
Information
Abstract
Spiking neural P systems (in short, SN P systems) are models of computation inspired by biological spiking neurons. SN P systems have neurons as spike processors which are placed on the nodes of a directed and static graph (the edges in the graph are the synapses). In this work, we introduce a variant called SN P systems with scheduled synapses (in short, SSN P systems). SSN P systems are inspired and motivated by the structural dynamism of biological synapses, while incorporating ideas from nonstatic (ie dynamic) graphs and networks. In particular, synapses in SSN P systems are available only at specific durations according to their schedules. The SSN P systems model is a response to the problem of introducing durations to synapses of SN P systems. Since SN P systems are in essence static graphs, it is natural to consider them for dynamic graphs also.
International
Si
JCR
Si
Title
Ieee Transactions on Nanobioscience
ISBN
1536-1241
Impact factor JCR
2,771
Impact info
Volume
Journal number
From page
888
To page
895
Month
SIN MES
Ranking
Participants
  • Autor: Francis George Cabarle
  • Autor: Henry Adorna
  • Autor: Min Jiang
  • Autor: Xiangxiang Zeng (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial
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Cofinanciación del MINECO en el marco del Programa INNCIDE 2011 (OTR-2011-0236)
Cofinanciación del MINECO en el marco del Programa INNPACTO (IPT-020000-2010-22)