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The design of neuron-bipolar junction transistor (vBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templates

dc.citation.epage200en_US
dc.citation.spage195en_US
dc.contributor.authorYen, WCen_US
dc.contributor.authorWu, CYen_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.date.accessioned2014-12-08T15:26:59Z
dc.date.available2014-12-08T15:26:59Z
dc.date.issued2000en_US
dc.description.abstractA compact and efficient neuron-bipolar junction transistor (vBJT) cellular neural network(CNN) structure with multi-neighborhood-layer templates is proposed and analyzed Using the proposed structure, the coefficients ol the templates with two neighborhood layers are fully realizable. But those with more than two neighborhood layers ore constrained. As the demonstrative examples on the applications of the proposed vBJT CNNs, the functions of both de-blurring and muller-lyer arrowhead illusion functions have been successfully realized and verified by HSPICE simulation.en_US
dc.identifier.isbn0-7803-6344-2en_US
dc.identifier.journalPROCEEDINGS OF THE 2000 6TH IEEE INTERNATIONAL WORKSHOP ON CELLULAR NEURAL NETWORKS AND THEIR APPLICATIONS (CNNA 2000)en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/19220
dc.identifier.wosnumberWOS:000166182700034
dc.language.isoen_USen_US
dc.titleThe design of neuron-bipolar junction transistor (vBJT) cellular neural network (CNN) structure with multi-neighborhood-layer templatesen_US
dc.typeProceedings Paperen_US

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