Nonlinear system identification

dc.contributor.advisorde Figueiredo, Rui J. P.en_US
dc.creatorNetravali, Arun Narayanen_US
dc.date.accessioned2016-04-22T21:58:11Zen_US
dc.date.available2016-04-22T21:58:11Zen_US
dc.date.issued1969en_US
dc.description.abstractStochastic approximation methods for the identification of parameters of nonlinear systems without dynamics have been widely discussed in the literature. In this work, two classes of discrete-time nonlinear dynamical systems driven by independent noise are considered. The measurements are assumed to be linear scalar and are made in the presence of independent noise. The systems under consideration are identified by the estimation of the parameters appearing in the evolution operator. These parameters are assumed to be constant during the identification time and they are estimated by means of stochastic approximation algorithms. A computer algorithm based on the above method is used to identify the parameters for some typical examples.en_US
dc.format.digitalOriginreformatted digitalen_US
dc.format.extent38 ppen_US
dc.identifier.callnoThesis E.E. 1969 NETRAVALIen_US
dc.identifier.citationNetravali, Arun Narayan. "Nonlinear system identification." (1969) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/89698">https://hdl.handle.net/1911/89698</a>.en_US
dc.identifier.digitalRICE0729en_US
dc.identifier.urihttps://hdl.handle.net/1911/89698en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.titleNonlinear system identificationen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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