CONSTRAINED AND REGULARIZED SYSTEMIDENTIFICATIONTor
نویسنده
چکیده
Prior knowledge can be introduced into system identiication problems in terms of constraints on the parameter space, or regularizing penalty functions in a prediction error criterion. The contribution of this work is mainly an extention of the well known FPE (Final Prediction Error) statistic to the case when the system identiication problem is constrainted and contains a regularization penalty. The FPECR statistic (Final Prediction Error with Constraints and Regularization) is of potential interest as a criterion for selection of both regularization parameters and structural parameters such as order.
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