Abstract
We propose a distributed sparse signal reconstruction algorithm in the full Bayesian framework by using Variational Bayesian(VB) with embedded consensus filter. Specifically, each node execute one-step average-consensus with its neighbors per VB step and thus reach a consensus on estimate of sparse signal finally. The proposed approach is ease of implementation and scalability to large networks. In addition, due to the observability of nodes can be enhanced by average-consensus, the number of measurements for each node can be further reduced and not necessary to satisfy lower bound required by CS. Simulation results demonstrate that the proposed distributed approach have good recovery performance and converge to their centralized counterpart.
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Zhao, Z., Pin, P., Yu, W. (2017). A Distributed Sparse Signal Reconstruction Algorithm in Wireless Sensor Network. In: Sun, X., Chao, HC., You, X., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2017. Lecture Notes in Computer Science(), vol 10602. Springer, Cham. https://doi.org/10.1007/978-3-319-68505-2_38
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DOI: https://doi.org/10.1007/978-3-319-68505-2_38
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