Statistical Identification of Kernels of Discrete Nonlinear Systems

dc.contributor.authorShcherbakov, M. A.
dc.coverage.issue1cs
dc.coverage.volume6cs
dc.date.accessioned2016-05-05T12:01:28Z
dc.date.available2016-05-05T12:01:28Z
dc.date.issued1997-04cs
dc.description.abstractA method for identification of discrete nonlinear systems in terms of the Volterra-Wiener series is presented. It is shown that use of a special, composite-frequency input signal as approximation to Gaussian noise provides a computational efficiency of this method, especially for high order kernels. Orthogonal functionals and consistent estimations for Wiener kernels in the frequency domains are derived for this class of noise input. A basis of the proposed computational procedure for practical identification is the fast Fourier transform (FFT) algorithm which is used both for a generating of system stimuluses and for an analysis of system reactions.en
dc.formattextcs
dc.format.extent16-18cs
dc.format.mimetypeapplication/pdfen
dc.identifier.citationRadioengineering. 1997, vol. 6, č. 1, s. 16-18. ISSN 1210-2512cs
dc.identifier.issn1210-2512
dc.identifier.urihttp://hdl.handle.net/11012/58357
dc.language.isoencs
dc.publisherSpolečnost pro radioelektronické inženýrstvícs
dc.relation.ispartofRadioengineeringcs
dc.relation.urihttp://www.radioeng.cz/fulltexts/1997/97_01_03.pdfcs
dc.rightsCreative Commons Attribution 3.0 Unported Licenseen
dc.rights.accessopenAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/en
dc.subjectnonlinear systemsen
dc.subjectidentificationen
dc.subjectVolterra-Wiener seriesen
dc.titleStatistical Identification of Kernels of Discrete Nonlinear Systemsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.affiliatedInstitution.facultyFakulta eletrotechniky a komunikačních technologiícs
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