Distributed adaptive estimation of correlated node-specific signals in a fully connected sensor network

Authors:
Alexander Bertrand;Marc Moonen
Affiliations:
Katholieke Universiteit Leuven - Dept. ESAT, Kasteelpark Arenberg 10, B-3001, Belgium;Katholieke Universiteit Leuven - Dept. ESAT, Kasteelpark Arenberg 10, B-3001, Belgium
Venue:
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Year:
2009

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Robust distributed noise reduction in hearing aids with external acoustic sensor nodes

EURASIP Journal on Advances in Signal Processing - Special issue on digital signal processing for hearing instruments
Distributed adaptive node-specific signal estimation in fully connected sensor networks-part I: sequential node updating

IEEE Transactions on Signal Processing
Distributed adaptive node-specific signal estimation in fully connected sensor networks-part II: simultaneous and asynchronous node updating

IEEE Transactions on Signal Processing

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Abstract

We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. The algorithm estimates node-specific signals at each node based on reduced-dimensionality sensor measurements of other nodes in the network. If the node-specific signals to be estimated are linearly dependent on a common latent process with a low dimension compared to the dimension of the sensor measurements, the algorithm can significantly reduce the required communication bandwidth and still provide the optimal linear estimator at each node as if all sensor measurements were available in every node. Because of its adaptive nature and fast convergence properties, the algorithm is suited for real-time applications in dynamic environments, such as speech enhancement in acoustic sensor networks.