Nonlinear system identification

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dc.contributor.advisorde Figueiredo, Rui J. P.
dc.creatorNetravali, Arun Narayan
dc.date.accessioned2016-04-22T21:58:11Z
dc.date.available2016-04-22T21:58:11Z
dc.date.issued1969
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.
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>.
dc.identifier.digitalRICE0729en_US
dc.identifier.urihttps://hdl.handle.net/1911/89698
dc.language.isoeng
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.
dc.titleNonlinear system identification
dc.typeThesis
dc.type.materialText
thesis.degree.departmentElectrical Engineering
thesis.degree.disciplineEngineering
thesis.degree.grantorRice University
thesis.degree.levelMasters
thesis.degree.nameMaster of Science
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