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...

In this paper, the problem of constructing the whole view of a scene background from an image sequence is considered. First, point or block correspondence between each pair of successive frames is determined. Three parametric motion models are used: 2-D translation with scale change, affine, and projective. Motion parameters are estimated using either robust criteria and the Levenberg–Marquardt...

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...

Inverse modeling seeks model parameters given a set of observations. However, for practical problems because the number of measurements is often large and the model parameters are also numerous, conventional methods for inverse modeling can be computationally expensive. We have developed a new, computationally efficient parallel Levenberg-Marquardt method for solving inverse modeling problems w...

We describe and analyse Levenberg–Marquardt methods for solving systems of nonlinear equations. More specifically, we first propose an adaptive formula for the Levenberg–Marquardt parameter and analyse the local convergence of the method under Hölder metric subregularity. We then introduce a bounded version of the Levenberg–Marquardt parameter and analyse the local convergence of the modified m...

Bundle Adjustment is a common technique to improve results of any multiple view reconstruction algorithm to obtain 3D structure for computer vision and computer graphics. If the error of a reconstruction can be expressed by an error function, this function can be minimized by numerical methods such as the Levenberg-Marquardt algorithm. By this means, the reconstruction can often be significantl...

In this paper, Levenberg-Marquardt (LM) learning algorithm for a single Integrate-and-Fire Neuron (IFN) is proposed and tested for various applications in which a neural network based on multilayer perceptron is conventionally used. It is found that a single IFN is sufficient for the applications that require a number of neurons in different hidden layers of a conventional neural network. Sever...