T. A. Condarcure

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Training of recurrent neural networks by conventional error backpropagation methods introduces considerable computational complexities due to the need for gradient evaluations. In this paper we shall present a training approach using concepts from the theory of stochastic learning automata that eliminates the need for computation of gradients and hence(More)
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