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The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model

Koeppl, H. and Josan, A. S. and Paoli, G. and Kubin, G. (2004):
The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model.
In: EURASIP Journal on Applied Signal Processing, pp. 1817-1830, 12, [Online-Edition: http://asp.eurasipjournals.com/content/2004/12/642938],
[Article]

Abstract

In linear system identification, optimal excitation signals can be determined using the Cramer-Rao bound. This problem has not been thoroughly studied for the nonlinear case. In this work, the Cramer-Rao bound for a factorisable Volterra model is derived. The analytical result is supported with simulation examples. The bound is then used to find the optimal excitation signal out of the class of discrete multitone signals. As the model is nonlinear in the parameters, the bound depends on the model parameters themselves. On this basis, a three-step identification procedure is proposed. To illustrate the procedure, signal optimisation is explicitly performed for a third-order nonlinear model. Methods of nonlinear optimisation are applied for the parameter estimation of the model. As a baseline, the problem of optimal discrete multitone signals for linear FIR filter estimation is reviewed.

Item Type: Article
Erschienen: 2004
Creators: Koeppl, H. and Josan, A. S. and Paoli, G. and Kubin, G.
Title: The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model
Language: English
Abstract:

In linear system identification, optimal excitation signals can be determined using the Cramer-Rao bound. This problem has not been thoroughly studied for the nonlinear case. In this work, the Cramer-Rao bound for a factorisable Volterra model is derived. The analytical result is supported with simulation examples. The bound is then used to find the optimal excitation signal out of the class of discrete multitone signals. As the model is nonlinear in the parameters, the bound depends on the model parameters themselves. On this basis, a three-step identification procedure is proposed. To illustrate the procedure, signal optimisation is explicitly performed for a third-order nonlinear model. Methods of nonlinear optimisation are applied for the parameter estimation of the model. As a baseline, the problem of optimal discrete multitone signals for linear FIR filter estimation is reviewed.

Journal or Publication Title: EURASIP Journal on Applied Signal Processing
Volume: 12
Divisions: 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems
18 Department of Electrical Engineering and Information Technology
18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications
Date Deposited: 04 Apr 2014 12:38
Official URL: http://asp.eurasipjournals.com/content/2004/12/642938
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