Abstract
In this paper, we suggest a neural network signal detector using radial basis function network for detecting a known signal in presence of Gaussian and non-Gaussian noise. We employ this RBF neural detector to detect the presence or absence of a known signal corrupted by different Gaussian and non-Gaussian noise components. In case of non-Gaussian noise, computer simulation results show that RBF network signal detector has significant improvement in performance characteristics. Detection capability is better than to those obtained with multilayer perceptrons and optimum matched filter detector
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