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This paper addresses the problem of joint multi-source localization and environment perception in wireless sensor networks (WSNs) based on received signal strength (RSS). Contrary to the traditional RSS approaches which assume known number of sources and known parameter of environments, we propose to estimate the sources with unknown number and the unknown environmental parameter simultaneously. By...
This paper addresses the problem of monitoring and discovering abnormalities in sensing fields with large-scale wireless sensor networks. By exploiting the sparsity of abnormalities, the signal recovery problem is expressed as an l-l regularized least squares formulation with nonnegative constraints. Furthermore, a decentralized Gauss-Seidel approach is proposed for in-network signal processing. Comparing...
Average consensus algorithms have attracted popularity in the wireless sensor network scenario as a simple way to compute linear combinations of the observations gathered by the sensors, in a totally decentralized fashion, i.e., without a fusion center. However, average consensus techniques involve the iterated exchange of data among sensors. In a practical implementation, this interaction is affected...
Non-parametric estimation of an unknown position parameter in a bandwidth-constrained wireless sensor network (WSN) is considered in this paper. Due to bandwidth constraint, each sensor is restricted to send only one bit of information to a fusion center. We propose a non-parametric estimator that employs a recently introduced adaptive quantization (AQ) scheme. Specifically, the position parameter...
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