142 Design and Optimization of Levenberg-Marquardt based Neural Network Classifier for EMG Signals to Identify Hand Motions Muhammad Ibn Ibrahimy, Md. Rezwanul Ahsan, Othman Omran Khalifa Dept. of ECE, Faculty of Engineering, International Islamic University Malaysia, 53100 Kuala Lumpur, Malaysia Dept. of Electrical Electronic and System Engineering, Faculty of Engineering and Built Environment...

This paper proposes a new Levenberg-Marquardt algorithm that is accelerated by adjusting a Jacobian matrix and a quasi-Hessian matrix. The proposed method partitions the Jacobian matrix into block matrices and employs the inverse of a partitioned matrix to find the inverse of the quasi-Hessian matrix. Our method can avoid expensive operations and save memory in calculating the inverse of the qu...

In this paper, we propose the block-diagonal matrix to approximate the Hessian matrix in the Levenberg Mar-quardt method in the training of neural networks. Two weight updating strategies, namely asynchronous and synchronous updating methods were investigated. Asyn-chronous method updates weights of one block at a time while synchronous method updates all weights at the same time. Variations of...

In the present work the Levenberg-Marquardt method (LM), Artificial Neural Networks (ANNs) and a hybridization ANN-LM are used for the solution of the inverse radiative transfer problem of estimating the space dependent albedo in one-dimensional heterogeneous participating media. The unknown function is expanded as a series of known functions, and a finite dimensional optimization problem is th...

In order to better understand the mechanical properties of biological cells, characterization and investigation of their material behavior is necessary. In this paper hyperelastic Neo-Hookean material is used to characterize the mechanical properties of mouse oocyte cell. It has been assumed that the cell behaves as continuous, isotropic, nonlinear and homogenous material for modeling. Then, by...

Multidimensional scaling (MDS) which is a fundamental problem in data analysis, can be formulated as a nonlinear global optimization problem. In order to solve it, some local, heuristic and global optimization methods are implemented. In another hand, to perform our new heuristic approach, the MDS problem is studied by using a multistart Levenberg-Marquardt method and, also for some small examp...

Owing to the highly complicated nature and the escalating cost involved in construction claims, it is highly desirable for the parties to a dispute to know with some certainty how the case would be resolved if it were taken to court. The use of artificial neural networks can be a cost-effective technique to help to predict the outcome of construction claims, on the basis of characteristics of c...

This paper presents a novel training algorithm for fuzzy inference systems. The algorithm combines the Levenberg-Marquardt algorithm with variable structure systems approach. The combination is performed by expressing the parameter update rule in continuous time and application of sliding control method to the gradient based training procedure. In this paper, it is discussed that a fuzzy infere...

This paper introduces a special arc spline called an Euler arc spline as the basic form for visually pleasing completion curves. It is considered as an extension of an Euler curve in the sense that the points in the Euler curve are replaced by arcs. A simple way for specifying it, which is suitable for shape completion, is presented. It is shown that Euler arc splines have several properties de...

The rst part of this paper studies a Levenberg-Marquardt scheme for nonlinear inverse problems where the corresponding Lagrange (or regularization) parameter is chosen from an inexact Newton strategy. While the convergence analysis of standard implementations based on trust region strategies always requires the invertibility of the Fr echet derivative of the nonlinear operator at the exact solu...