Online EM algorithm for jump Markov systems

Date

2012-07-09

Author

Zhao, Yuxin
Yin, Feng
Gunnarsson, Fredrik
Amirijoo, Mehdi
Özkan, Emre
Gustafsson, Fredrik

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The Expectation-Maximization (EM) algorithm in combination with particle filters is a powerful tool that can solve very complex problems, such as parameter estimation in general nonlinear non-Gaussian state space models. We here apply the recently proposed online EM algorithm to parameter estimation in jump Markov models, that contain both continuous and discrete states. In particular, we focus on estimating process and measurement noise distributions being modeled as mixtures of members from the exponential family.

URI

http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumber=5712016
https://hdl.handle.net/11511/75626
https://ieeexplore.ieee.org/document/6290538

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Department of Electrical and Electronics Engineering, Conference / Seminar