Memristor-based circuit implementation of pulse-coupled neural network with dynamical threshold generators

Xie, X; Wen, S; Zeng, Z; Huang, T

Memristor-based circuit implementation of pulse-coupled neural network with dynamical threshold generators

Xie, X Wen, S

Zeng, Z Huang, T

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Publisher:: ELSEVIER SCIENCE BV
Publication Type:: Journal Article
Citation:: Neurocomputing, 2018, 284, pp. 10-16
Issue Date:: 2018-04-05

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Field	Value	Language
dc.contributor.author	Xie, X
dc.contributor.author	Wen, S https://orcid.org/0000-0001-8077-7001
dc.contributor.author	Zeng, Z
dc.contributor.author	Huang, T
dc.date.accessioned	2022-09-04T07:26:08Z
dc.date.available	2022-09-04T07:26:08Z
dc.date.issued	2018-04-05
dc.identifier.citation	Neurocomputing, 2018, 284, pp. 10-16
dc.identifier.issn	0925-2312
dc.identifier.issn	1872-8286
dc.identifier.uri	http://hdl.handle.net/10453/161313
dc.description.abstract	Pulse-coupled neural network (PCNN) is inspired from the visual cortex of cats. It is superior to the traditional algorithm in the field of digital image processing. Meanwhile, memristor is considered as an important circuit element to implement brain intelligence hardware. In order to realize the memristor-based circuit of PCNN, a threshold generator is designed to dynamically update the memristance under input excitation with the exponential memristor model. Furthermore, the whole circuit of non-simplified pulse-coupled neural network is realized via memristor. Finally, the image processing function is demonstrated by the proposed circuit via simulation.
dc.language	English
dc.publisher	ELSEVIER SCIENCE BV
dc.relation	National Natural Science Foundation of China61673187
dc.relation.ispartof	Neurocomputing
dc.relation.isbasedon	10.1016/j.neucom.2018.01.024
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 17 Psychology and Cognitive Sciences
dc.subject.classification	Artificial Intelligence & Image Processing
dc.title	Memristor-based circuit implementation of pulse-coupled neural network with dynamical threshold generators
dc.type	Journal Article
utslib.citation.volume	284
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	17 Psychology and Cognitive Sciences
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/Strength - AAII - Australian Artificial Intelligence Institute
utslib.copyright.status	closed_access	*
dc.date.updated	2022-09-04T07:26:07Z
pubs.publication-status	Published
pubs.volume	284

Abstract:

Pulse-coupled neural network (PCNN) is inspired from the visual cortex of cats. It is superior to the traditional algorithm in the field of digital image processing. Meanwhile, memristor is considered as an important circuit element to implement brain intelligence hardware. In order to realize the memristor-based circuit of PCNN, a threshold generator is designed to dynamically update the memristance under input excitation with the exponential memristor model. Furthermore, the whole circuit of non-simplified pulse-coupled neural network is realized via memristor. Finally, the image processing function is demonstrated by the proposed circuit via simulation.

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http://hdl.handle.net/10453/161313