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Polynomial filtering of discrete-time stochastic linear systems with multiplicative state noise

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3 Author(s)
Carravetta, F. ; Istituto di Analisi dei Sistemi ed Inf., CNR, Rome, Italy ; Germani, A. ; Raimondi, N.

The problem of finding an optimal polynomial state estimate for the class of stochastic linear models with a multiplicative state noise term is studied. For such models, a technique of state augmentation is used, leading to the definition of a general polynomial filter. The theory is developed for time-varying systems with nonstationary and non-Gaussian noises. Moreover, the steady-state polynomial filter for stationary systems is also studied. Numerical simulations show the high performances of the proposed method with respect to the classical linear filtering techniques

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Automatic Control, IEEE Transactions on  (Volume:42 ,  Issue: 8 )