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Maximum likelihood estimation of the identification parameters and its correction

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3 Author(s)
An Kai ; Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610041, P. R. China ; Ma Jiaguang ; Fu Chengyu

By taking the subsequence out of the input-output sequence of a system polluted by white noise, an independent observation sequence and its probability density are obtained and then a maximum likelihood estimation of the identification parameters is given. In order to decrease the asymptotic error, a corrector of maximum likelihood. (CML) estimation with its recursive algorithm is given. It has been proved that the corrector has smaller asymptotic error than the least square methods. A simulation example shows that the corrector of maximum likelihood estimation is of higher approximating precision to the true parameters than the least SQuare methods.

Published in:

Journal of Systems Engineering and Electronics  (Volume:13 ,  Issue: 4 )