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Recent developments in optimal bounding ellipsoidal parameter estimation

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  • Rao, Ashok K.
  • Huang, Yih-Fang

Abstract

The Optimal Bounding Ellipsoid (OBE) algorithms are viable alternatives to conventional adaptive filtering algorithms in situations where the noise does not satisfy the usual stationarity and whiteness assumptions. An example is shown in which the performance of an OBE algorithm is seen to be markedly superior to that of the recursive least-squares algorithm. Subsequently, an overview of some recent work in the area of OBE parameter estimation is presented. A lattice filter implementation of one particular OBE algorithm is first described. The extension of the OBE algorithm to the estimation of parameters of ARMA models is performed and the results of a convergence analysis are presented. It is demonstrated through a simulation example that the transient performance of the proposed algorithm is superior to that of the well-known extended least-squares algorithm.

Suggested Citation

  • Rao, Ashok K. & Huang, Yih-Fang, 1990. "Recent developments in optimal bounding ellipsoidal parameter estimation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 32(5), pages 515-526.
    • Handle: RePEc:eee:matcom:v:32:y:1990:i:5:p:515-526
    DOI: 10.1016/0378-4754(90)90007-6
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    Cited by:

    1. Walter, Eric & Piet-Lahanier, Hélène, 1990. "Estimation of parameter bounds from bounded-error data: a survey," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 32(5), pages 449-468.

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