Deployment of Sensors According to Quasi-Random and Well Distributed Sequences for Nonparametric Estimation of Spatial Means of Random Fields
Overview & Synopsis
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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Document Information
| Document Title | Deployment of Sensors According to Quasi-Random and Well Distributed Sequences for Nonparametric Estimation of Spatial Means of Random Fields |
|---|---|
| Author / Organization | Ewa Skubalska-Rafajłowicz, Ewaryst Rafajłowicz |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2013 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-37564 |
| Original Source Link | Visit Source Page on hal.science » |