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Least squares based recursive identification for stochastic systems with colored noises
Wang Dongqing*
College of Automation Engineering, Qingdao University, Qingdao, 266071, China

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Abstract�� An auxiliary model and least squares based recursive identification algorithm was presented for stochastic systems with colored noises. The basic idea is, by means of the auxiliary model identification principle and extended least squares identification theory, to replace the unknown variables in the information vector with the outputs of the auxiliary model and to replace the unmeasurable noise terms with the estimated residuals, and then to propose a recursive identification algorithm to estimate all parameters of the systems, including the parameters of the noise models. The simulation results indicate that the algorithm is effective.
Keywords�� recursive identification   parameter estimation   least squares   stochastic systems     
Received 2007-12-03;


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������.һ����ɫ�����������ϵͳ��С���˵��Ʊ�ʶ[J]  �������պ����ѧѧ��, 2008,V34(8): 935-939
Wang Dongqing.Least squares based recursive identification for stochastic systems with colored noises[J]  JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2008,V34(8): 935-939
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