Influence of Training Set Selection in Artificial Neural Network-Based Propagation Path Loss Predictions
Data(s) |
31/05/2013
31/05/2013
2012
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Resumo |
This paper analyzes the use of artificial neural networks (ANNs) for predicting the received power/path loss in both outdoor and indoor links. The approach followed has been a combined use of ANNs and ray-tracing, the latter allowing the identification and parameterization of the so-called dominant path. A complete description of the process for creating and training an ANN-based model is presented with special emphasis on the training process. More specifically, we will be discussing various techniques to arrive at valid predictions focusing on an optimum selection of the training set. A quantitative analysis based on results from two narrowband measurement campaigns, one outdoors and the other indoors, is also presented. |
Identificador |
International Journal of Antennas and Propagation 2012 : (2012) // Article ID 351487 1687-5869 http://hdl.handle.net/10810/10176 10.1155/2012/351487 |
Idioma(s) |
eng |
Publicador |
Hindawi Publishing Corporation |
Relação |
http://www.hindawi.com/journals/ijap/2012/351487/ |
Direitos |
© 2012 Ignacio Fernández Anitzine et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. info:eu-repo/semantics/openAccess |
Tipo |
info:eu-repo/semantics/article |