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In this article, artificial neural networks are applied to data measured on a wireless indoor mobile communications scenario for 768 MHz transmission. Three multilayer perceptron (MLP) with backpropagation are applied to predict the signal power level in an environment with downlink (base station-to-mobile) wireless propagation. The MLP networks improve the general prediction when compared to traditional prediction models for both metrics used. |
