%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