Internal print

Šmídl V., Quinn A.

Interní publikace DAR -

ÚTIA AV ČR 2005/34

ÚTIA AV ĆR

Praha

2005

4

Ing. Václav Šmídl, Ph.D. (ÚTIA - Oddělení adaptivních systémů)

Variational Bayes Approximation in Bayesian Filtering. [file]

The Variational Bayes (VB) approximation is applied in the context of Bayesian filtering, yielding a tractable on-line scheme for a wide range of non-stationary parametric models. This VB-filtering scheme is used to identify a Hidden Markov Model with an unknown non-stationary transition matrix. In a simulation study involving soft-bit data, reliable inference of the underlying binary sequence is achieved in tandem with estimation of the transition probabilities. Its performance compares favourably with a proposed particle filtering approach, and at lower computational cost.