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Abstract:
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In this paper, a comparison study among three neuralnetwork
algorithms for the synthesis of array patterns is presented. The
neural networks are used to estimate the array elements' excitations for
an arbitrary pattern. The architecture of the neural networks is discussed
and simulation results are presented. Two new neural networks,
based on radial basis functions (RBFs) and wavelet neural networks
(WNNs), are introduced. The proposed networks offer a more efficient
synthesis procedure, as compared to other available techniques |