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...

We present a fast, accurate and robust parallel Levenberg-Marquardt minimization optimizer, GPU-LMFit, which is implemented on graphics processing unit for high performance scalable parallel model fitting processing. GPU-LMFit can provide a dramatic speed-up in massive model fitting analyses to enable real-time automated pixel-wise parametric imaging microscopy. We demonstrate the performance o...

In this paper, the feedforward neural network with Levenberg-Marquardt backpropagation training algorithm is used to predict the grasping forces according to the multisensory signals as training samples for specific design of underactuated multifingered hand to avoid the complexity of calculating the inverse kinematics which is appeared through the dynamic modeling of the robotic hand and prepa...

A smooth nonlinear system identification method without resorting to on-line parameter estimation is presented. Based on the radial basis function, a signal-dependent ARX (RBF-ARX) model is established to describe the nonlinear system dynamics. Especially, a new structured nonlinear parameter optimization algorithm based on the Levenberg-Marquardt algorithm and the least squares method is propo...

An extraction method for the parameters of a new analytical model of the submicron MOS transistor for analog applications is presented. The stages which form the extraction process are detailed, along with an original parameter extractor created in Labview, which uses the Levenberg-Marquardt fitting algorithm. Also presented are the results of the fitting of the model to experimental curves obt...

A new algorithm for the solution of large-scale nonlinear complementarity problems is introduced. The algorithm is based on a nonsmooth equation reformulation of the complementarity problem and on an inexact Levenberg-Marquardt-type algorithm for its solution. Under mild assumptions, and requiring only the approximate solution of a linear system at each iteration, the algorithm is shown to be b...

A program is described for carrying out leastsquares camera modelling and scene reconstruction from a set of image and scene measurements of geometric features. Because of the object-oriented nature of the program, it is easily extendible to include very general types of camera, image feature or measurement. A Levenberg-Marquardt parameter estimation algorithm is used to optimize the choice 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 this paper, we adopt the Levenberg-Marquardt (LM) algorithm to implement the nonlinear multivariable optimization for azimuth/elevation angle-of-arrival (AOA) estimation based on the Capon beamforming algorithm. The formulation is based on the fact that the cost function of the Capon algorithm can be expressed in a least-squares form. The performance in terms of the root mean square error (R...

In this paper, a Rough-Neuro hybrid methodology of the diagnostic process is proposed as a means to achieve accurate diagnosing of Erythemato-Squamous diseases. The methodology incorporates a two-stage hybrid mechanism. Rough sets Johnson Reducer for reduction of relevant attributes and artificial neural network Levenberg-Marquardt algorithm for the classification of the diseases. The model ach...