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Artificial neural networks (ANN)-based models are efficient ways of source localization. However very large training sets are needed to precisely estimate two-dimension DOA with ANN models. In this paper we present a fast artificial neural network approach for 2D DOA estimation with reduced training sets sizes. We exploit the symmetry properties of UCA arrays to build two different datasets for elevation...
In this paper we present a Linear Vector Quan-tization (LVQ) neural network approach to estimate Direction of Arrivals (DOA) of narrowband sources. It is shown that appropriately trained LVQ networks along with a specific postprocessing scheme can successfully be used for DOA estimation purposes. We take advantage of the execution speed of LVQ algorithm to accurately classify an incoming signal on...
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