Neural network Levenberg-Marquardt method

Learning involves thus designating the miiumum of the error function. For this purpose, we usually apply gradient methods (conjugate gradients), based on the Hessian matrix (Newton, Levenberg-Marquardt methods), or on approximation of the inverse of the Hessian matrix (quasi-Newton methods) [2]. The MLP neural network is sensu stricte a static model, but it is possible to introduce dynamics... 

T. Takeo, P.K. Mahanta, Why C.T.C. tea is less fragrant Two and a Bud 30, 76-77 (1983) B.G. Kermani, S.S. Schiffman, H.T. Nagle, Performance of the Levenberg-Marquardt neural network training method in electronic nose applications. Sens. Actuators B Chem. 110, 13-22 (2005)... 

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