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Modelling and analysis of spiking neural P systems with anti-spikes using Pnet lab
Kamala Krithivasan
Published in
2011
Volume: 2
   
Issue: 2-3
Pages: 141 - 149
Abstract
Petri Nets are promising methods for modelling and simulating biological systems. Spiking Neural P system with anti-spikes (SN PA systems) is a biologically inspired computing model that incorporates two types of objects called spikes and anti-spikes thus representing binary information in a natural way. In this paper, we propose a methodology to simulate SN PA systems using a Petri net tool called Pnet Lab. It provides a promising way for SN PA systems because of its parallel execution semantics and appropriateness to represent typical working processes of these systems. This enables us to verify system properties, system soundness and to simulate the dynamic behaviour. © 2011 Elsevier Ltd.
About the journal
JournalNano Communication Networks
ISSN18787789
Open AccessNo
Concepts (14)
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    Binary information
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    BIOLOGICALLY INSPIRED
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    Computing model
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    Dynamic behaviours
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    Modelling
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    Parallel executions
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    PNET LAB
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    SPIKING NEURAL P SYSTEMS
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    System property
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    WORKING PROCESS
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    Petri nets
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    PUBLIC ADDRESS SYSTEMS
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    Semantics
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    Biological systems