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Modeling and estimation of discrete-time Gaussian reciprocal processes

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3 Author(s)
B. C. Levy ; Dept. of Electr. Eng. & Comput. Sci., California Univ., Davis, CA, USA ; R. Frezza ; A. J. Krener

Discrete-time Gaussian reciprocal processes are characterized in terms of a second-order two-point boundary-value nearest-neighbor model driven by a locally correlated noise whose correlation is specified by the model dynamics. This second-order model is the analog for reciprocal processes of the standard first-order state-space models for Markov processes. The model is used to obtain a solution to the smoothing problem for reciprocal processes. The resulting smoother obeys second-order equations whose structure is similar to that of the Kalman filter for Gauss-Markov processes. It is shown that the smoothing error is itself a reciprocal process

Published in:

IEEE Transactions on Automatic Control  (Volume:35 ,  Issue: 9 )