Result: Normal forms for spiking neural P systems
Title:
Normal forms for spiking neural P systems
Authors:
Source:
Membrane ComputingTheoretical computer science. 372(2-3):196-217
Publisher Information:
Amsterdam: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 10 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Sciences biologiques et medicales, Biological and medical sciences, Sciences biologiques fondamentales et appliquees. Psychologie, Fundamental and applied biological sciences. Psychology, Generalites, General aspects, Mathématiques biologiques. Statistiques. Modèles. Métrologie. Informatique en biologie (généralités), Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects), Calcul automatique, Computing, Cálculo automático, Complexité, Complexity, Complejidad, Complétude, Completeness, Completitud, Expression régulière, Regular expression, Expresión regular, Forme normale, Normal form, Forma normal, Informatique théorique, Computer theory, Informática teórica, Simplification, Simplificación, Synapse, Sinapsis, Calcul membrane, Membrane computing, Neurone impulsionnel, Spiking neuron, Système P, P system, Universalité, Universality, Spiking neural P system
Document Type:
Conference
Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science. University of California, Santa Barbara, CA 93106, United States
Department of Computer Science, Louisiana Tech University, Ruston, PO Box 10348, Louisiana, LA-71272, United States
Universidad Politécnica de Madrid -UPM, Faculdad de Informdtica, Campus de Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain
Institute of Mathematics of the Romanian Academy, PO Box 1-764, 014700 BucureŞti, Romania
Department of Computer Science and Artificial Intelligence, University of Sevilla, Avda. Reina Mercedes s/n, 41012 Sevilla, Spain
Institute of Computer Science, Silesian University, 74601 Opava, Czech Republic
Department of Computer Science, Louisiana Tech University, Ruston, PO Box 10348, Louisiana, LA-71272, United States
Universidad Politécnica de Madrid -UPM, Faculdad de Informdtica, Campus de Montegancedo s/n, Boadilla del Monte, 28660 Madrid, Spain
Institute of Mathematics of the Romanian Academy, PO Box 1-764, 014700 BucureŞti, Romania
Department of Computer Science and Artificial Intelligence, University of Sevilla, Avda. Reina Mercedes s/n, 41012 Sevilla, Spain
Institute of Computer Science, Silesian University, 74601 Opava, Czech Republic
ISSN:
0304-3975
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods
Computer science; theoretical automation; systems
Generalities in biological sciences
Computer science; theoretical automation; systems
Generalities in biological sciences
Accession Number:
edscal.18619487
Database:
PASCAL Archive
Further Information
The spiking neural P systems are a class of computing devices recently introduced as a bridge between spiking neural nets and membrane computing. In this paper we prove a series of normal forms for spiking neural P systems, concerning the regular expressions used in the firing rules, the delay between firing and spiking, the forgetting rules used, and the outdegree of the graph of synapses. In all cases, surprising simplifications are found, without losing the computational completeness - sometimes at the price of (slightly) increasing other parameters which describe the complexity of these systems.