This paper describes the efficient MPPT tracking for variable wind speed using an artificial neural network. The network has been trained backpropagation algorithm and Levenberg-Marquardt (LM) based optimization technique to achieve maximum power point. A multilevel inverter having 10 switches used reduce voltage stress, THD switching losses resulting in improvement performance reduction driver...

In-situ bioremediation is one of the most economic techniques for groundwater remediation. BIOPLUME III is used to simulate the transport and biodegradation of contaminant. During optimal design of bioremediation system, the simulated BIOPLUME III data for the entire aquifer is usually called several times by optimization algorithm to optimize the system. This is a very time consuming process a...

We present the formulation and implementation of an image stabilization system capable of stabilizing video with very large displacements between frames. A coarse-tone technique is applied in resolution and in model spaces. The registration algorithm uses phase correlation to obtain an initial estimate for translation between images; then Levenberg-Marquardt method for non-linear optimization i...

Rational filter functions improve convergence of contour-based eigensolvers, a popular algorithm family for the solution of the interior eigenvalue problem. We present an optimization method of these rational filters in the Least-Squares sense. Our filters out-perform existing filters on a large and representative problem set, which we show on the example of FEAST. We provide a framework for (n...

The Levenberg-Marquardt algorithm is one of the most popular algorithms for the solution of nonlinear least squares problems. In this paper, we propose and analyze the global and local convergence results of a novel Levenberg-Marquadt method for solving general nonlinear least squares problems. The proposed algorithm enjoys strong convergence properties (global convergence as well as quadratic ...

We present regularization tools for training small, medium and large feed-forward artiicial neural networks. The determination of the weights leads to very ill-conditioned nonlinear least squares problems and regularization is often suggested to get control over the network complexity, small variance error, and to get a nice optimization problem. The algorithms proposed explicitly use a sequenc...

*This research was carried out as part of NWO research project 611-304-019, 'Address: Free University, Department of Economics and Econometrics, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands. E-mail: [email protected].

In this paper, a Levenberg-Marquardt inspired sliding mode control theory based adaptation laws are proposed to train an intelligent fuzzy neural network controller for a quadrotor aircraft. The proposed controller is used to control and stabilize a quadrotor unmanned aerial vehicle in the presence of periodic wind gust. A proportional-derivative controller is firstly introduced based on which ...

ISSN 2277-5064 | © 2013 Bonfring Abstract--This paper presents a neural network based on Levenberg-Marquardt back-propagation algorithm for prediction of degree of angiographic coronary heart disease. The novelty of this work is training a one hidden layer neural network with Levenberg-Marquardt back-propagation algorithm for multivariate large dataset. An ANN model is developed for prediction ...