A Variant of Back-propagation Algorithm for Multilayer Feed-forward Network
نویسندگان
چکیده
In this paper, a variant of Backpropagation algorithm is proposed for feed-forward neural networks learning. The proposed algorithm improve the backpropagation training in terms of quick convergence of the solution depending on the slope of the error graph and increase the speed of convergence of the system. Simulations are conducted to compare and evaluate the convergence behavior and the speed factor of the proposed algorithm with existing Backpropagation algorithm. Simulation results of large-scale classical neuralnetwork benchmarks are presented which reveal the power of the proposed algorithm to obtain actual solutions.
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