The Complementary Model in Continuous/Discrete Smoothing
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We consider the problem of smoothing a continuous-time random process using irregularly spaced noisy samples. If the random process to be smoothed is generated by a linear state model, the relevant Hamiltonian system can be easily derived using the concept of complementary model, introduced by Weinert and Desai . All smoothing algorithms can then be obtained via various changes of variables in the Hamiltonian system.
KeywordsHamiltonian System Smoothing Algorithm Linear State Model Complementary Model Noisy Sample
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