a new approach utilizing newton method and homotopy analysis method (ham) is proposed for solving nonlinear system of equations. accelerating the rate of convergence of ham, and obtaining a global quadratic rate of convergence are the main purposes of this approach. the numerical results demonstrate the efficiency and the performance of proposed approach. the comparison with conventional homoto...

The classical inexact Newton algorithm is an efficient and popular technique for solving large sparse nonlinear system of equations. When the nonlinearities in the system are wellbalanced, a near quadratic convergence is often observed, however, if some of the equations are much more nonlinear than the others in the system, the convergence is much slower. The slow convergence (or sometimes dive...

Background: Infertility effects on psychological and emotional tension in couples and make severe stress in infertile men and women. Relaxation technique is one of the methods which reduce stress and balance human emotions. The purpose of this study was determination of relaxation effect on stress score in the infertile women and pregnancy test as outcome of their treatment. Materials and Metho...

Various distributed optimization methods have been developed for consensus optimization problems in multi-agent networks. Most of these methods only use gradient or subgradient information of the objective functions, which suffer from slow convergence rate. Recently, a distributed Newton method whose appeal stems from the use of second-order information and its fast convergence rate has been de...

The adjoint Newton algorithm (ANA) is based on the firstand second-order adjoint techniques allowing one to obtain the ‘‘Newton line search direction’’ by integrating a ‘‘tangent linear model’’ backward in time (with negative time steps). Moreover, the ANA provides a new technique to find Newton line search direction without using gradient information. The error present in approximating the Hes...

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We present an estimate approach to compute the viscoplastic behavior of a polymeric composite under different thermomechanical approaches. This investagation incorporates computational neural network as the tool for determining the creep behaviour of the composite. We propose a new second-order learning algorithm for training the multilayer networks. Training in the neural network is generally ...

A new approach to the problem of minimizing L2sensitivity subject to L2-norm scaling constraints for state-space digital filters is proposed. Using linearalgebraic techniques, the problem at hand is converted into an unconstrained optimization problem, and the unconstrained problem obtained is then solved by applying an efficient quasi-Newton algorithm. Computer simulation results are presented...

A new technique is used instead of the classical majorant principle to analyze the R-order of convergence of the Newton process when more general conditions than the Kantorovich ones are considered. © 2005 Elsevier B.V. All rights reserved. MSC: 47H17; 65J15

this study concerns with a trust-region-based method for solving unconstrained optimization problems. the approach takes the advantages of the compact limited memory bfgs updating formula together with an appropriate adaptive radius strategy. in our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-newt...