Abstract
A novel algorithm is studied for the identification of linear-in-parameters models. This technique is dubbed Quasi-OBE (QOBE) because it is based on the principles of optimal bounding ellipsoid (OBE) identification, but has other geometric and classic least-squares interpretations that enhance its interpretability and application potential. Convergence behavior of both the central point estimate and measures of the hyperellipsoidal membership-set will be discussed in general terms, particularly in comparison with several conventional OBE algorithms. The QOBE algorithm uses highly-selective updating and exhibits excellent tracking ability in time-varying environments.
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