Recent developments in optimal bounding ellipsoidal parameter estimation

Ashok K. Rao and Yih-Fang Huang

Mathematics and Computers in Simulation (MATCOM), 1990, vol. 32, issue 5, 515-526

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.

Date: 1990
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:32:y:1990:i:5:p:515-526

DOI: 10.1016/0378-4754(90)90007-6

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