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The system identification problem is researched when the input and output signal are both corrupted by noise. The robust least square (RLS) method and its application to parameter estimation problem, in which the perturbations are unknown but bounded (UBB), are introduced. The method can be interpreted as Tikhonov regularization procedure, with the(More)
A problem of multi-sensor robust information fusion for uncertain systems with colored noises is investigated. A new multi-sensor optimal information fusion steady-state robust filter weighted by matrix and scalars with uncertain parameters is given using robust filter theory based on linear least variance information fusion criterion. Compared with(More)
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