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There are many successful applications of Backpropagation (BP) for training multilayer neural networks. However, they have many shortcomings. Learning often takes insupportable time to converge, and it may fall into local minima at all. One of the possible remedies to escape from local minima is using a very small learning rate, but this will slow the learning process. The proposed algorithm is presented for the training of multilayer neural networks with very small learning rate, especiallydoi:10.28945/866 fatcat:zf4342yegfbqzfwbkt3hfdlody