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Sparse Point Source Estimation in Sensor Networks with Gaussian Kernels

机译:高斯核在传感器网络中的稀疏点源估计

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In this paper we present a technique for the estimation of point sources in a diffusive environment that can be applied to wireless sensor networks. It is based on methods from the field of sparse recovery, using Gaussian kernels as basis functions. After presenting the underlying physical process, a linear system model is developed out of it. For the estimation of its unknown parameters, solution approaches are presented. The approach is verified by means of numerical simulations. Furthermore, we indicate ways to perform a distributed estimation of the parameters within the network.
机译:在本文中,我们提出了一种可在扩散环境中估算点源的技术,该技术可应用于无线传感器网络。它基于稀疏恢复领域的方法,使用高斯核作为基础函数。在介绍了基本的物理过程之后,就可以开发出线性系统模型。为了估计其未知参数,提出了解决方法。通过数值模拟验证了该方法。此外,我们指出了执行网络内参数的分布式估计的方法。

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