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This paper presents an adaptive implementation of the functional-link neural network (FLNN) architecture together with a supervised learning algorithm that rapidly determines the weights of the network. The proposed algorithm is able to achieve 'one-shot' training as opposed to iterative training algorithms in the literature. Also discussed is a stepwise updating algorithm that updates the weights...
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