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A Distributed Sparse Signal Reconstruction Algorithm in Wireless Sensor Network

机译：无线传感器网络中的分布式稀疏信号重构算法

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摘要

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.
机译：通过使用带有嵌入共识滤波器的变分贝叶斯（VB），我们在完整的贝叶斯框架中提出了一种分布式稀疏信号重建算法。具体来说，每个节点在每个VB步骤中与其邻居执行一个一步的平均共识，从而最终就稀疏信号的估计达成共识。所提出的方法易于实现并且可扩展到大型网络。另外，由于可以通过平均共识来提高节点的可观察性，因此可以进一步减少每个节点的测量次数，并且不必满足CS要求的下限。仿真结果表明，所提出的分布式方法具有良好的恢复性能，并收敛于集中式方法。

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