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A distributed algorithm for robust LCMV beamforming
2016
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
In this paper we propose a distributed reformulation of the linearly constrained minimum variance (LCMV) beamformer for use in acoustic wireless sensor networks. The proposed distributed minimum variance (DMV) algorithm, for which we demonstrate implementations for both cyclic and acyclic networks, allows the optimal beamformer output to be computed at each node without the need for sharing raw data within the network. By exploiting the low rank structure of estimated covariance matrices in
doi:10.1109/icassp.2016.7471645
dblp:conf/icassp/ShersonKH16
fatcat:ardgmnk27rbsfnumdqrtlszi54