Gaussian information matrix for Wiener model identification

Kaushik Mahata; Johan Schoukens

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arXiv · 1510.03013

Gaussian information matrix for Wiener model identification

Kaushik Mahata·Johan Schoukens

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Abstract

We present a closed form expression for the information matrix associated with the Wiener model identification problem under the assumption that the input signal is a stationary Gaussian process. This expression holds under quite generic assumptions. We allow the linear sub-system to have a rational transfer function of arbitrary order, and the static nonlinearity to be a polynomial of arbitrary degree. We also present a simple expression for the determinant of the information matrix. The expressions presented herein has been used for optimal experiment design for Wiener model identification.

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Kaushik Mahata, Johan Schoukens. 2015-10-11. Gaussian information matrix for Wiener model identification. https://arxiv.org/abs/1510.03013

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