Identification of parameters in distributed parameter systems by regularization

Abstract

Identification of spatially varying parameters in distributed parameter systems from noisy data is an ill-posed problem. The concept of regularization, widely used in solving linear Fredholm integral equations, is developed for the identification of parameters in distributed parameter systems. A general regularization identification theory is first presented and then applied to a parabolic identification problem. Methods for the numerical implementation of the regularization identification approach are also presented.

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