dc.contributor.author | Asyali, M.H. | |
dc.contributor.author | Alci, M. | |
dc.contributor.editor | | |
dc.date.accessioned | 2021-01-25T20:52:11Z | |
dc.date.available | 2021-01-25T20:52:11Z | |
dc.date.issued | 2007 | |
dc.identifier | 10.1007/978-3-540-36841-0_11 | |
dc.identifier.issn | 16800737 | |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84907879147&doi=10.1007%2f978-3-540-36841-0_11&partnerID=40&md5=920291528159978885ce15abc22e2e8c | |
dc.identifier.uri | https://dspace.yasar.edu.tr/xmlui/handle/20.500.12742/10762 | |
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 | IFMBE Proceedings | |
dc.title | Obtaining volterra kernels from neural networks | |
dc.type | Conference Paper | |
dc.relation.firstpage | 11 | |
dc.relation.lastpage | 15 | |
dc.relation.volume | 14 | |
dc.relation.issue | 1 | |
dc.description.affiliations | Yasar University, Computer Engineering Dept, Bornova, Izmir, Turkey; Ege University, Electrical and Electronics Engineering Dept, Bornova, Izmir, Turkey | |