Bayesian estimation of mixtures with dynamic transitions and known component parameters

Title:

Bayesian estimation of mixtures with dynamic transitions and known component parameters

Creator:

Ivan, Suzdaleva, Evgenia, and Kárný, Miroslav

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:18c1fb74-efd0-44fd-9942-0f2f054c1ae1
uuid:18c1fb74-efd0-44fd-9942-0f2f054c1ae1

Subject:

mixture model, Bayesian estimation, approximation, clustering, and classification

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

Probabilistic mixtures provide flexible "universal'' approximation of probability density functions. Their wide use is enabled by the availability of a range of efficient estimation algorithms. Among them, quasi-Bayesian estimation plays a prominent role as it runs "naturally'' in one-pass mode. This is important in on-line applications and/or extensive databases. It even copes with dynamic nature of components forming the mixture. However, the quasi-Bayesian estimation relies on mixing via constant component weights. Thus, mixtures with dynamic components and dynamic transitions between them are not supported. The present paper fills this gap. For the sake of simplicity and to give a better insight into the task, the paper considers mixtures with known components. A general case with unknown components will be presented soon.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Coverage:

[572]-594

Source:

Kybernetika | 2011 Volume:47 | Number:4

Harvested from:

CDK

Metadata only:

false