Good Learning Performance of Backpropagation Algorithm with Chaotic Noise Features
نویسندگان
چکیده
Over the years, many improvements and modifications of the backpropagation learning algorithm have been reported. In this study, we propose a new modified backpropagation learning algorithm by adding the chaotic noise into weight update process. By computer simulations, we confirm that the proposed algorithm can gives a better convergence rate and can find a good solution in early time compared to the conventional backpropagation algorithm. Weight update position, noise amplitude and control parameter of chaos can give a big effect on the backpropagation learning performance.
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