In this paper we develop a convergence analysis in an infinite dimensional setting of the Levenberg–Marquardt iteration for the solution of a hybrid conductivity imaging problem. The problem consists in determining the spatially varying conductivity from a series of measurements of power densities for various voltage inductions. Although this problem has been very well studied in the literature...

Patterns have emerged as an efficient way to communicate solution proposals. Most software patterns up to now focus on logical design issues. This article presents physical design patterns, that partly employ existing logical patterns. The presented patterns deal with limited physical resources, and framework development. "Advent", combined with the logical "Light'n'Heavy", facilitates online i...

In this work, we describe a method for the classification of respiratory states based on four significant features using Artificial neural network (ANN). These features are extracted from the respiratory signals using modified threshold algorithm were fed as input parameters to the ANN for classification. A gradient based search algorithms are usually being used in ANN to find a set of suitable...

We propose a new optimizer in the context of multimodal image registration. The optimized criterion is the mutual information between the images to align. This criterion requires that their joint histogram be available. For its computation, we introduce differentiable and separable Parzen windows that satisfy the partition of unity. Along with a continuous model of the images based on splines, ...

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 ...

In this paper Artificial Neural Network (ANN) is used to predict the solar irradiation in Djibouti for the first Time that is useful to the integration of Concentrating Solar Power (CSP) and sites selections for new or future solar plants as part of solar energy development. An ANN algorithm was developed to establish a forward/reverse correspondence between the latitude, longitude, altitude an...

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...

For managing data in a smart card’s limited memory, containing medical and biometric images, images compression is resorted to. For image retrieval, it is necessary that the classification algorithm be efficient to search and locate the image in a compressed domain. This study proposes a novel training algorithm for Multi-Layer Perceptron Neural Network (MLP-NN) to classify compressed images. M...

In this work, a recursive Levenberg-Marquardt (LM) learning algorithm in the complex domain is developed and applied to the learning of an adaptive control scheme composed by ComplexValued Recurrent Neural Networks (CVRNN). We simplified the derivation of the LM learning algorithm using a diagrammatic method to derive the adjoint CVRNN used to obtain the gradient terms. Furthermore, we apply th...

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 ...