Obtaining Volterra Kernels from Neural Networks

dc.contributor.author	Asyali, M.H.
dc.contributor.author	Alci, M.
dc.date.accessioned	2021-01-25T19:36:55Z
dc.date.available	2021-01-25T19:36:55Z
dc.date.issued	2007
dc.identifier.issn	1680-0737
dc.identifier.uri	https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/8391
dc.description.abstract	Both neural networks (NN) and Volterra series (VS) are widely used in nonlinear dynamic system identification. In VS approach, the system is modeled using a set of kernel functions that correspond to different order convolutions. Kernels in VS are typical
dc.language.iso	English
dc.publisher	SPRINGER-VERLAG BERLIN
dc.title	Obtaining Volterra Kernels from Neural Networks
dc.type	Proceedings Paper
dc.relation.firstpage	11
dc.relation.lastpage	+
dc.relation.volume	14
dc.description.woscategory	Engineering, Biomedical; Physics, Applied; Imaging Science & Photographic Technology
dc.description.wosresearcharea	Engineering; Physics; Imaging Science & Photographic Technology
dc.identifier.wosid	WOS:000260855900001
dc.identifier.ctitle	World Congress on Medical Physics and Biomedical Engineering
dc.identifier.cdate	AUG 27-SEP 01, 2006

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