It has recently been seen that the cost of numerically solving linear systems of equations in which the coeecient matrix is equi-variant with respect to a permutation group ? can be signiicantly reduced via the method of symmetry reduction. For systems in which the coeecient matrix is not equivariant, the numerical solving can be accelerated by using the ?-equivariant part of the coeecient matr...

Newton-HSS methods, that are variants of inexact Newton methods different from Newton-Krylov methods, have been shown to be competitive methods for solving large sparse systems of nonlinear equations with positive definite Jacobian matrices [Bai and Guo, 2010]. In that paper, only local convergence was proved. In this paper, we prove a Kantorovich-type semilocal convergence. Then we introduce N...

Many problems in science and engineering must solve nonlinear necessary conditions for defining meaningful solutions. For example, a standard problem in optimization involves solving for the roots of nonlinear functions defined by f(x) = 0, where x is the unknown variable. Classically one develops a first-order Taylor series model which provides the necessary condition that must be iteratively ...

Image registration is a very important problem in computer vision and medical image processing. Numerous algorithms for registering single and multi-modal image data have been reported in these areas. Robustness as well as computational efficiency are prime factors of importance in image data registration. In this paper, a robust/reliable and efficient algorithm for estimating the transformatio...

Within the multibody systems literature, few attempts have been made to use automatic differentiation for solving forward multibody dynamics and evaluating its computational efficiency. The most relevant implementations are found in the sensitivity analysis field, but they rarely address automatic differentiation issues in depth. This paper presents a thorough analysis of automatic differentiat...