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Deployment of Sensors According to Quasi-Random and Well Distributed Sequences for Nonparametric Estimation of Spatial Means of Random Fields

机译:随机场空间均值的非参数估计的准随机和均匀分布序列的传感器部署

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Our aim is to discuss advantages of quasi-random points (also known as uniformly distributed (UD) points) and their sub-class recently proposed by the authors that are well-distributed (WD) as sensors' positions in estimating the spatial mean. UD and WD s sequences have many interesting properties that are useful both for wireless sensors networks (coverage an and connectivity) and for large area networks such as radiological or environment pollution monitoring stations. In opposite to most popular parameter estimation approaches, we consider a nonparametric estimator of the spatial mean. We shall prove the estimator convergence in the integrated mean square-error sense.
机译:我们的目的是讨论准随机点(也称为均匀分布(UD)点)的优点及其作者最近提出的子类,这些子类在估计空间均值时作为传感器的位置而分布良好(WD)。 UD和WD的序列具有许多有趣的属性,这些属性对于无线传感器网络(覆盖和连接)以及诸如放射或环境污染监测站之类的广域网都是有用的。与最流行的参数估计方法相反,我们考虑空间均值的非参数估计器。我们将在综合均方误差意义上证明估计量的收敛性。

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