HOPFIELD-TANK NEURAL NET - WALSH TO FOURIER-TRANSFORM

KARRAS, DA; VAROUFAKIS, SJ; ANTONIOU, GE; CARAYANNIS, GB

dc.contributor.author	KARRAS, DA	en
dc.contributor.author	VAROUFAKIS, SJ	en
dc.contributor.author	ANTONIOU, GE	en
dc.contributor.author	CARAYANNIS, GB	en
dc.date.accessioned	2014-03-01T01:41:26Z
dc.date.available	2014-03-01T01:41:26Z
dc.date.issued	1992	en
dc.identifier.issn	0925-2312	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/23492
dc.subject	NEURAL NETWORKS	en
dc.subject	HOPFIELD-TANK MODEL	en
dc.subject	WALSH TRANSFORM	en
dc.subject	FOURIER TRANSFORM	en
dc.subject.classification	Computer Science, Artificial Intelligence	en
dc.title	HOPFIELD-TANK NEURAL NET - WALSH TO FOURIER-TRANSFORM	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	1992	en
heal.abstract	A simple method for the computation of the Discrete Fourier Transform (DFT) from the Walsh Transform, using the Neural Network model of Hopfield and Tank, is presented. The proposed method circumvents the algorithmic complexity of the DFT. The computation time for the evaluation of the DFT coefficients depends upon a time constant which characterizes the neural network.	en
heal.publisher	ELSEVIER SCIENCE BV	en
heal.journalName	NEUROCOMPUTING	en
dc.identifier.isi	ISI:A1992JD95000006	en
dc.identifier.volume	4	en
dc.identifier.issue	1-2	en
dc.identifier.spage	37	en
dc.identifier.epage	41	en