Institute of Information Theory and Automation

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Distributed dynamic estimation in diffusion networks

Agency: 
GACR
Identification Code: 
GP14-06678P
Start: 
2014-01-01
End: 
2016-12-31
Project Focus: 
teoretický
Project Type (EU): 
other
Abstract: 
The project aims to develop a dynamic distributed estimation framework, intended for fully distributed low-cost parameter estimation of stationary signals and reduced-complexity tracking of nonstationary processes. Being designed for diffusion networks, where each network node can use information provided by neighbor nodes, it will not rely on the existence of a dedicated fusion center, nor a Hamiltonian cycle. The framework will be formulated abstractly in the Bayesian paradigm, allowing, in contrast to current single problem-oriented methods, its direct application to a large class of different problems, comprising dynamic distributed (auto) regression, classification, reliability estimation etc. The developed methods will be efficient in terms of computational and communication resources. Their robustness to network elements degradation and failures is an inherent part of the solution.
Publications ÚTIA: 
list
2014-04-02 10:26