Deployment of Sensors According to Quasi-Random and Well Distributed Sequences for Nonparametric Estimation of Spatial Means of Random Fields - IFIP AICT 443: System Modeling and Optimization
Conference Papers Year : 2014

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

Ewa Skubalska-Rafajłowicz
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Ewaryst Rafajłowicz
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Abstract

Our aim is to discuss advantages of quasi-random points (also known as uniformly distributed (UD) points [8]) and their sub-class recently proposed by the authors [17] that are well-distributed (WD) as sensors’ positions in estimating the spatial mean. UD and WDs 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.
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hal-01286440 , version 1 (10-03-2016)

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Ewa Skubalska-Rafajłowicz, Ewaryst Rafajłowicz. Deployment of Sensors According to Quasi-Random and Well Distributed Sequences for Nonparametric Estimation of Spatial Means of Random Fields. 26th Conference on System Modeling and Optimization (CSMO), Sep 2013, Klagenfurt, Austria. pp.306-316, ⟨10.1007/978-3-662-45504-3_30⟩. ⟨hal-01286440⟩
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