A Method of Accelerating Neural Network Learning

摘要

The article presents of accelerating neural network learning by the Back Propagation algorithm and one of its fastest modifications – the Levenberg–Marqurdt method. The learning is accelerated by introducing the ‘single-direction’ coefficient of the change of x for calculating its new values (the number of iterations is decreased by approximately 30%). Simulation results of learning neural networks by applying both the classic method and the method of accelerating the procedure are presented.