The Complementary Model in Continuous/Discrete Smoothing

Conference paper
Part of the Lecture Notes in Statistics book series (LNS, volume 25)


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 [1]. All smoothing algorithms can then be obtained via various changes of variables in the Hamiltonian system.


Hamiltonian System Smoothing Algorithm Linear State Model Complementary Model Noisy Sample 
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Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  1. 1.Department of Electrical Engineering and Computer ScienceThe Johns Hopkins UniversityBaltimoreUSA

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