Titlebook: Bounding Approaches to System Identification; Mario Milanese,John Norton,éric Walter Book 1996 Springer Science+Business Media New York 19

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Transfer Function Parameter Interval Estimation Using Recursive Least Squares in the Time and Frequmodel (or RLS model), where the equation error is assumed to lie between a known upper and lower bound. It is shown that the off-line least squares method gives the maximum and minimum parameter values that could have produced the recorded input-output sequence. By modifying the RLS estimator in two

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Arbitrary

Linear Interpolation and Estimation Using Interval Analysis, the solution set (not the parameter set). It characterizes and presents the bounding functions for the solution set using interval arithmetic. Numerical algorithms with result verification and corresponding programs for the computation of the bounding functions in given domain are reported. Some ex

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Adaptive Approximation of Uncertainty Sets for Linear Regression Models,etric/non-parametric (restricted complexity) models. The hypothesis is that disturbance information and prior knowledge on the unmodeled dynamics are available as deterministic bounds. A procedure is proposed for constructing recursively an outer bounding parallelotopic estimate of the parameter unc

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Worst-Case ,, Identification,aluation of the identification errors, the design of experiment, the selection of the model structure, the construction of optimal and almost optimal algorithms, and the convergence properties of the identification algorithms.

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