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Computational power of sequential dendrite P systems

Authors :
Xiaohui Luo
Tingting Bao
Hong Peng
Qian Yang
Jun Wang
Xiaoxiao Song
Source :
Theoretical Computer Science. 893:133-145
Publication Year :
2021
Publisher :
Elsevier BV, 2021.

Abstract

Dendrite P (DeP) systems are a new variant of neural-like P systems, abstracted by the information processing and feedback mechanisms of dendrites. In the variant, a global block is assumed to synchronize all of neurons, hence, DeP systems work in synchronous mode. This paper investigates sequential version of the variant, that is, sequential dendrite P (SDeP) systems. Based on maximum number of spikes in neurons, two sequential modes are distinguished: max-sequentiality and max-pseudo-sequentiality strategies. SDeP systems have two interesting and recognizable features: (i) it behaves as a firing-storing process; (ii) cooperative firing mechanism. The computational completeness of SDeP systems is discussed. We prove that SDeP systems can be used as Turing universal number generating/accepting devices for max-sequentiality and max-pseudo-sequentiality strategies. We also establish a small universal function computing device of SDeP systems with 91 neurons in max-sequentiality strategy.

Details

ISSN :
03043975
Volume :
893
Database :
OpenAIRE
Journal :
Theoretical Computer Science
Accession number :
edsair.doi...........7c3923a5f70653b7ff3fc150040dc9db