Stochastic Approximation for Identification of Multivariable Systems
| dc.contributor.advisor | Sinha, N.K. | |
| dc.contributor.author | El-Sherief, Hossny E. | |
| dc.contributor.department | Electrical Engineering | en_US |
| dc.date.accessioned | 2015-07-09T22:41:18Z | |
| dc.date.available | 2015-07-09T22:41:18Z | |
| dc.date.issued | 1977-03 | |
| dc.description.abstract | <p> In this thesis a non-parametric normalized stochastic approximation algorithm has been developed for the identification of multivariable systems from noisy data without prior knowledge of the statistics of measurement noise.</p> <p> The system model is first transformed into a special canonical form, then it is formulated in a non-parametric form. The parameters of this model are estimated through a normalized stochastic approximation algorithm. Finally, the system parameters are recovered from these estimates by another transformation.</p> <p> The proposed algorithm is applied to the identification of two simulated systems.</p> <p> Conclusions of this work and suggestions for future work are given.</p> | en_US |
| dc.description.degree | Master of Engineering (MEngr) | en_US |
| dc.description.degreetype | Thesis | en_US |
| dc.identifier.uri | http://hdl.handle.net/11375/17707 | |
| dc.language.iso | en_US | en_US |
| dc.subject | non-parametric, stochastic, approximation, multivariable, identification | en_US |
| dc.title | Stochastic Approximation for Identification of Multivariable Systems | en_US |
| dc.type | Thesis | en_US |