We study the convergence of general abstract descent methods applied to a lower semicontinuous nonconvex function f that satisfies the KurdykaLojasiewicz inequality in a Hilbert space. We prove that any precompact sequence converges to a critical point of f and obtain new convergence rates both for the values and the iterates. The analysis covers alternating versions of the forward-backward met...

We study the convergence of general abstract descent methods applied to a lower semicontinuous nonconvex function f that satisfies the KurdykaLojasiewicz inequality in a Hilbert space. We prove that any precompact sequence converges to a critical point of f and obtain new convergence rates both for the values and the iterates. The analysis covers alternating versions of the forward-backward met...

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...

BP Neural Network has a longer training time and a slow convergence. To deal with the defects of BP Neural Network a modified BP algorithm is proposed in the paper. The algorithm is applied for the control of Inverted Pendulum, a highly non linear system inherently being open loop unstable. Levenberg-Marquardt algorithm is used for the training purpose. The training samples are being collected ...

Performance of four types of functionally different artificial neural network (ANN) models, namely Feed forward neural network, Elman type recurrent neural network, Input delay neural network and Radial basis function network and fourteen types of algorithms, namely Batch gradient descent (traingd), Batch gradient descent with momentum (traingdm), Adaptive learning rate (traingda), Adaptive lea...

Introduction: Energy resolving X-ray photon counting detectors are able to assign each detected photon to energy bins [1] (Figure 1). This allows the decomposition of an X-ray image into the materials of the acquired object [1, 2], which has potential benefits in angiography. Contrast agent can be extracted without acquiring a mask image, possibly saving dose and avoiding problems with patient ...

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 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 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...

This paper describes artificial neural network (ANN) based prediction of theresponse of a fiber optic sensor using evanescent field absorption (EFA). The sensingprobe of the sensor is made up a bundle of five PCS fibers to maximize the interaction ofevanescent field with the absorbing medium. Different backpropagation algorithms areused to train the multilayer perceptron ANN. The Levenberg-Marq...