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Please use this identifier to cite or link to this item: http://eprint.iitd.ac.in/handle/2074/1552

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dc.contributor.authorPrasad, R-
dc.contributor.authorSinha, A-
dc.identifier.citationAutomatic Control, IEEE Transactions on, 22(4), 671 - 672en
dc.description.abstractA two-stage state and parameter estimation algorithm for linear systems has been developed. Stage 1 uses a stochastic approximation method for state estimation, while stage 2 considers parameter estimation through a linear Kalman filter. These two stages are coupled in a bootstrap manner. The algorithm is computationally much simpler than the usual extended Kalman filter. A fourth-order numerical example has been solved, and results have been compared with those obtained using an extended Kalman filter.en
dc.format.extent33588 bytes-
dc.subjectparameter estimation algorithmen
dc.subjectlinear systemsen
dc.subjectstochastic approximationen
dc.subjectparameter estimationen
dc.subjectbootstrap manneren
dc.titleOn bootstrap identification using stochastic approximationen
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