%0 Conference Paper %A Asirvadam, V.S. %D 2008 %F scholars:423 %K Neural networks; Recursive functions; Technical presentations, Levenberg-marquardt; Multilayer perceptions; Novel applications; Parameter corrections; Recursive neural networks, Adaptive algorithms %P 89-94 %R 10.1109/CSEW.2008.55 %T Adaptive regularizer for recursive neural network training algorithms %U https://khub.utp.edu.my/scholars/423/ %X Adaptive Marquardt parameter correction techniques are tested for recursive Levenberg-Marquardt (RLM) and proposed novel application on decomposed recursive Levenberg Marquardt (DRLM) algorithms. The adaptive Marquardt correction is based on recursive moving-window residual. Experiment results show superior convergence using decomposed approach and a slight improvement in performance by adopting the adaptive Marquardt correction on a fixed size multilayer perceptions (MLP) network. © 2008 IEEE. %Z cited By 6; Conference of 11th IEEE International Conference on Computational Science and Engineering, CSE Workshops 2008 ; Conference Date: 16 July 2008 Through 18 July 2008; Conference Code:73977