Cell-Like Spiking Neural P Systems With Request Rules.
- Publisher:
- Institute of Electrical and Electronics Engineers
- Publication Type:
- Journal Article
- Citation:
- IEEE Transactions on NanoBioscience, 2017, 16, (6), pp. 513-522
- Issue Date:
- 2017-09
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Filename | Description | Size | |||
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Cell-Like_Spiking_Neural_P_Systems_With_Request_Rules.pdf | 1.1 MB | Adobe PDF |
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Full metadata record
Field | Value | Language |
---|---|---|
dc.contributor.author | Pan, L | |
dc.contributor.author | Wu, T | |
dc.contributor.author | Su, Y | |
dc.contributor.author | Vasilakos, AV | |
dc.date.accessioned | 2022-08-23T04:35:38Z | |
dc.date.available | 2022-08-23T04:35:38Z | |
dc.date.issued | 2017-09 | |
dc.identifier.citation | IEEE Transactions on NanoBioscience, 2017, 16, (6), pp. 513-522 | |
dc.identifier.issn | 1536-1241 | |
dc.identifier.issn | 1558-2639 | |
dc.identifier.uri | http://hdl.handle.net/10453/160736 | |
dc.description.abstract | Cell-like spiking neural (cSN) P systems are a class of distributed and parallel computation models inspired by both the way in which neurons process information and communicate to each other by means of spikes and the compartmentalized structures of living cells. cSN P systems have been proved to be Turing universal if more spikes can be produced by consuming some spikes or spikes can be replicated. In this paper, in order to answer the open problem whether this functioning of producing more spikes and replicating spikes can be avoided by using some strategy without the loss of computation power, we introduce cSN P systems with request rules, which have classical spiking rules and forgetting rules, and also request rules in the skin membrane. The skin membrane can receive spikes from the environment by the application of request rules. cSN P systems with request rules are proved to be Turing universal. The results show that the decrease of computation power caused by removing the internal functioning of producing more spikes and replicating spikes can be compensated by request rules, which suggests that the communication between a cell and the environment is an essential ingredient of systems in terms of computation power. | |
dc.format | Print-Electronic | |
dc.language | eng | |
dc.publisher | Institute of Electrical and Electronics Engineers | |
dc.relation.ispartof | IEEE Transactions on NanoBioscience | |
dc.relation.isbasedon | 10.1109/TNB.2017.2722466 | |
dc.rights | info:eu-repo/semantics/closedAccess | |
dc.subject | 0801 Artificial Intelligence and Image Processing, 0903 Biomedical Engineering, 0906 Electrical and Electronic Engineering | |
dc.subject.classification | Nanoscience & Nanotechnology | |
dc.subject.mesh | Action Potentials | |
dc.subject.mesh | Animals | |
dc.subject.mesh | Biomimetics | |
dc.subject.mesh | Computer Simulation | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Models, Neurological | |
dc.subject.mesh | Nerve Net | |
dc.subject.mesh | Neural Networks, Computer | |
dc.subject.mesh | Neurons | |
dc.subject.mesh | Synaptic Transmission | |
dc.subject.mesh | Action Potentials | |
dc.subject.mesh | Animals | |
dc.subject.mesh | Biomimetics | |
dc.subject.mesh | Computer Simulation | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Models, Neurological | |
dc.subject.mesh | Nerve Net | |
dc.subject.mesh | Neural Networks, Computer | |
dc.subject.mesh | Neurons | |
dc.subject.mesh | Synaptic Transmission | |
dc.subject.mesh | Nerve Net | |
dc.subject.mesh | Neurons | |
dc.subject.mesh | Animals | |
dc.subject.mesh | Humans | |
dc.subject.mesh | Biomimetics | |
dc.subject.mesh | Synaptic Transmission | |
dc.subject.mesh | Action Potentials | |
dc.subject.mesh | Models, Neurological | |
dc.subject.mesh | Computer Simulation | |
dc.subject.mesh | Neural Networks, Computer | |
dc.title | Cell-Like Spiking Neural P Systems With Request Rules. | |
dc.type | Journal Article | |
utslib.citation.volume | 16 | |
utslib.location.activity | United States | |
utslib.for | 0801 Artificial Intelligence and Image Processing | |
utslib.for | 0903 Biomedical Engineering | |
utslib.for | 0906 Electrical and Electronic Engineering | |
pubs.organisational-group | /University of Technology Sydney | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology | |
pubs.organisational-group | /University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering | |
utslib.copyright.status | closed_access | * |
pubs.consider-herdc | false | |
dc.date.updated | 2022-08-23T04:35:37Z | |
pubs.issue | 6 | |
pubs.publication-status | Published | |
pubs.volume | 16 | |
utslib.citation.issue | 6 |
Abstract:
Cell-like spiking neural (cSN) P systems are a class of distributed and parallel computation models inspired by both the way in which neurons process information and communicate to each other by means of spikes and the compartmentalized structures of living cells. cSN P systems have been proved to be Turing universal if more spikes can be produced by consuming some spikes or spikes can be replicated. In this paper, in order to answer the open problem whether this functioning of producing more spikes and replicating spikes can be avoided by using some strategy without the loss of computation power, we introduce cSN P systems with request rules, which have classical spiking rules and forgetting rules, and also request rules in the skin membrane. The skin membrane can receive spikes from the environment by the application of request rules. cSN P systems with request rules are proved to be Turing universal. The results show that the decrease of computation power caused by removing the internal functioning of producing more spikes and replicating spikes can be compensated by request rules, which suggests that the communication between a cell and the environment is an essential ingredient of systems in terms of computation power.
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