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dc.contributor.authorBaktır, I. A.en_US
dc.contributor.authorTan, M. A.en_US
dc.date.accessioned2016-02-08T10:54:27Z
dc.date.available2016-02-08T10:54:27Z
dc.date.issued1993en_US
dc.identifier.issn1057-7130
dc.identifier.urihttp://hdl.handle.net/11693/26062
dc.description.abstractThe analog CMOS circuit realization of cellular neural networks with transconductance elements is presented. This realization can be easily adapted to various types of applications in image processing just by choosing the appropriate transconductance parameters according to the predetermined coefficients. The effectiveness of the designed circuits for connected component detection is shown by HSPICE simulations. For “fixed function” cellular neural network circuits the number of transistors are reduced further by using multi-input transconductance elements.en_US
dc.language.isoEnglishen_US
dc.source.titleIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processingen_US
dc.relation.isversionofhttp://dx.doi.org/10.1109/82.222819en_US
dc.subjectCMOS integrated circuitsen_US
dc.subjectElectric network analysisen_US
dc.subjectImage processingen_US
dc.subjectVLSI circuitsen_US
dc.subjectAnalog CMOS implementationen_US
dc.subjectCellular neural networksen_US
dc.subjectTransconductance elementsen_US
dc.subjectNeural networksen_US
dc.titleAnalog CMOS implementation of cellular neural networksen_US
dc.typeArticleen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage200en_US
dc.citation.epage206en_US
dc.citation.volumeNumber40en_US
dc.citation.issueNumber3en_US
dc.identifier.doi10.1109/82.222819en_US
dc.publisherIEEEen_US


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