Institute of Information Theory and Automation

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Conference Paper (international conference)

Diffusion filtration with approximate Bayesian computation

Dedecius Kamil, Djurić P. M.

: Proceedings of 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), p. 3207-3211

: 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015), (Brisbane, AU, 19.05.2015-24.05.2015)

: GP14-06678P, GA ČR

: Bayesian filtration, diffusion, distributed filtration

: 10.1109/ICASSP.2015.7178563

: http://library.utia.cas.cz/separaty/2015/AS/dedecius-0443931.pdf

(eng): Distributed filtration of state-space models with sensor networks assumes knowledge of a model of the data-generating process. However, this assumption is often violated in practice, as the conditions vary from node to node and are usually only partially known. In addition, the model may generally be too complicated, computationally demanding or even completely intractable. In this contribution, we propose a distributed filtration framework based on the novel approximate Bayesian computation (ABC) methods, which is able to overcome these issues. In particular, we focus on filtration in diffusion networks, where neighboring nodes share their observations and posterior distributions.

: BB

: 10103

2019-01-07 08:39