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An online parameter estimator for quick convergence and time-varying linear systems

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3 Author(s)
Wiberg, D.M. ; Dept. of Electr. Eng., California Univ., Los Angeles, CA, USA ; Powell, T.D. ; Ljungquist, Dag

A recursive algorithm called 3-OM is presented to estimate parameters and noise variances for discrete-time linear stochastic systems. The unprojected version of 3-OM is globally convergent with probability 1 to minima of the asymptotic negative log-likelihood function. 3-OM approximates the quick convergence attained by the optimal nonlinear filter used as a parameter estimator. The state-space form of 3-OM permits application to time-varying linear systems and to online tuning of a Kalman filter.

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Automatic Control, IEEE Transactions on  (Volume:45 ,  Issue: 10 )