Transcription of Levenberg–Marquardt Training
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Levenberg–Marquardt Training
IntroductionThe levenberg marquardt algorithm [L44,M63], which was independently developed by Kenneth levenberg and Donald marquardt , provides a numerical solution to the problem of minimizing a non-linear function. It is fast and has stable convergence. In the artificial neural-networks field, this algo-rithm is suitable for Training small- and medium-sized other methods have already been developed for neural-networks Training . The steep-est descent algorithm, also known as the error backpropagation (EBP) algorithm [EHW86,J88], dispersed the dark clouds on the field of artificial neural networks and could be regarded as one of the most significant breakthroughs for Training neural networks.
The Levenberg–Marquardt algorithm [L44,M63], which was independently developed by Kenneth Levenberg and Donald Marquardt, provides a numerical solution to the problem of minimizing a non-linear function. It is fast and has stable convergence. In the artificial neural-networks field, this algo-
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