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Memorias de investigación
Research Publications in journals:
Polynomial Complexity Classes in Spiking Neural P Systems
Year:2010
Research Areas
  • Information technology and adata processing
Information
Abstract
We study the computational potential of spiking neural (SN) P systems. several intractable problems have been proven to be solvable by these systems in polynomial or even constant time. We study first their formal aspects such as the input encoding, halting versus spiking, and descriptional complexity. Then we establish a formal platform for complexity classes of uniform families of confluent recognizer SN P sys- tems. Finally, we present results characterizing the computational power of several variants of confluent SN P systems, characterized by classes ranging from P to PSPACE.
International
Si
JCR
No
Title
Lecture notes in computer science
ISBN
0302-9743
Impact factor JCR
0
Impact info
Volume
Journal number
From page
348
To page
360
Month
ENERO
Ranking
Participants
  • Autor: Petr Sosik (UPM)
  • Autor: Alfonso Vicente Rodriguez-Paton Aradas (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
S2i 2020 Observatorio de investigación @ UPM con la colaboración del Consejo Social UPM
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)