An Algorithm for Fast Convergence in Training Neural Networks
نویسندگان
چکیده
In this work, two modifications on Levenberg-Marquardt algorithm for feedforward neural networks are studied. One modification is made on performance index, while the other one is on calculating gradient information. The modified algorithm gives a better convergence rate compared to the standard Levenberg-Marquard (LM) method and is less computationally intensive and requires less memory. The performance of the algorithm has been checked on several example problems.
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تاریخ انتشار 2001