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Presented is a nonlinear autoencoder, which reduces the dimensionality of a radio map, and consequently contributes to the reduction of the power consumption of client devices in a fingerprint-based indoor localisation. The nonlinear encoder shows significantly better performance in reducing the dimensionality than principal component analysis, a representative linear technique, did.
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