Convergence Analysis of an Iterative Targeting Method for Keyhole Robotic Surgery

AN ITERATIVE METHOD WITH SIX-ORDER CONVERGENCE FOR SOLVING NONLINEAR EQUATIONS

Modification of Newtons method with higher-order convergence is presented. The modification of Newtons method is based on Frontinis three-order method. The new method requires two-step per iteration. Analysis of convergence demonstrates that the order of convergence is 6. Some numerical examples illustrate that the algorithm is more efficient and performs better than classical Newtons method and ...

Convergence Analysis of an Iterative Correlation-based Controller Tuning Method

A new iterative method using closed-loop data for controller tuning based on the correlation approach is proposed. The main idea is to make the output error between the closed-loop system and a reference model uncorrelated with the reference signal. The controller parameters are calculated as the solution to a correlation equation involving instrumental variables. Convergence and consistency of...

Convergence Analysis of Preconditioned AOR Iterative Method for Linear Systems

MHmatrices appear in many areas of science and engineering, for example, in the solution of the linear complementarity problem LCP in optimization theory and in the solution of large systems for real-time changes of data in fluid analysis in car industry. Classical stationary iterative methods used for the solution of linear systems have been shown to convergence for this class of matrices. In ...

Convergence of an Iterative Method for Total Variation Denoising

In total variation denoising, one attempts to remove noise from a signal or image by solving a nonlinear minimization problem involving a total variation criterion. Several approaches based on this idea have recently been shown to be very eeective, particularly for denoising functions with discontinuities. This paper analyzes the convergence of an iterative method for solving such problems. The...

On the Convergence for an Iterative Method for Quasivariational Inclusions