The Restricted Variational Bayes approximation in Bayesian filtering

被引：0

作者：

Smidl, Vaclav ^{[1
]}

Quinn, Anthony ^{[2
]}

机构：

[1] Acad Sci, Prague, Czech Republic

[2] Trinity Coll Dublin, Dublin, Ireland

来源：

NSSPW: NONLINEAR STATISTICAL SIGNAL PROCESSING WORKSHOP: CLASSICAL, UNSCENTED AND PARTICLE FILTERING METHODS | 2006年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The Variational Bayes (VB) approach is used as a one-step approximation for Bayesian filtering. It requires the availability of moments of the free-form distributional optimizers. The latter may have intractable functional forms. In this contribution, we replace these by appropriate fixed-form distributions yielding the required moments. We address two scenarios of this Restricted VB (RVB) approximation. For the first scenario, an application in identification of HMMs is given. Close relationship of the second scenario to Rao-Blackwellized particle filtering is discussed and their performance is illustrated on a simple non-linear model.

引用

页码：224 / +

页数：2

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