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A Kalman filter type of extension to a deterministic gradient technique for parameter estimation

Author

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  • Smith, M.W.A.
  • Roberts, A.P.

Abstract

It is shown that a method for the identification of deterministic systems derived from the Kalman filter is related to a gradient technique of parameter estimation and that the range of problems to which the gradient method may be applied is thereby extended. Various versions of the discrete-time algorithm are compared from theoretical and computational points of view and also contrasted with the continuous-time algorithm. An important outcome is that the system containing unknown parameters and the identification algorithm may be formulated with one in discrete-time and the other in continuous-time.

Suggested Citation

  • Smith, M.W.A. & Roberts, A.P., 1978. "A Kalman filter type of extension to a deterministic gradient technique for parameter estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 20(4), pages 291-300.
    • Handle: RePEc:eee:matcom:v:20:y:1978:i:4:p:291-300
    DOI: 10.1016/0378-4754(78)90021-6
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    References listed on IDEAS

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    1. Smith, M.W.A. & Roberts, A.P., 1978. "An exact equivalence between the discrete- and continuous-time formulations of the Kalman filter," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 20(2), pages 102-109.
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