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Descripción
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| Nonparametric belief propagation (NBP) is the well-known method for cooperative localization in wireless sensor networks. It is capable to provide information about location estimation with appropriate uncertainty and to accommodate non-Gaussian distance measurement errors. However, the accuracy of NBP is questionable in loopy networks. Therefore, in this paper, we propose a novel approach, NBP based on spanning trees (NBP-ST) created by breadth first search (BFS) method. In addition, we propose a reliable indoor model based on obtained received-signal-strength (RSS) measurements in our lab. According to our experimental results, NBP-ST performs better than NBP in terms of accuracy and communication cost in the networks with high connectivity (i.e., highly loopy networks). | |
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Internacional
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Si |
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Nombre congreso
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International Conference on Sensor Technologies and Applications |
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Tipo de participación
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960 |
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Lugar del congreso
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Revisores
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Si |
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ISBN o ISSN
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978-1-4244-7538-4 |
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DOI
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10.1109/SENSORCOMM.2010.44 |
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Fecha inicio congreso
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18/07/2010 |
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Fecha fin congreso
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25/07/2010 |
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Desde la página
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238 |
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Hasta la página
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243 |
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Título de las actas
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IEEE proceedings of International Conference on Sensor Technologies and Applications |