Adaptive signal processing for ARX system disturbed by complex noise

Authors:
Yulai Zhang;Guiming Luo
Affiliations:
School of Software, Tsinghua University, Beijing, China;School of Software, Tsinghua University, Beijing, China
Venue:
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part I
Year:
2010

Citing 2
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System identification (2nd ed.): theory for the user

System identification (2nd ed.): theory for the user
Identification of ARX systems with non-stationary inputs - asymptotic analysis with application to adaptive input design

Automatica (Journal of IFAC)

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Abstract

The inverse of the Fisher information matrix can be decided by the system input sequence and the disturbance variance if a Gaussian noise is involved. The lower bound mean-square error matrix of any unbiased estimator is given by Cramer-Rao Lemma. When a system is disturbed by some biased noises, the classical Fisher information matrix would be not valid. The bound is not fitted when a biased estimator is implemented. Signal processing for ARX model disturbed by complex noise is concerned in this paper. Cramer-Rao bound of a biased estimation is obtained. An adaptive signal processing algorithm for identification of ARX system disturbed by biased estimation is proposed. Some experiments are included to verify the efficiency of the new algorithm.