This book is on conjugate gradient methods for unconstrained optimization. The concept of
conjugacy was introduced by Magnus Hestenes and Garrett Birkhoff in 1936 in the context of …

In this study, a new computing paradigm is presented for evaluation of dynamics of
nonlinear prey–predator mathematical model by exploiting the strengths of integrated …

In this work, an intelligent computing algorithm is developed for finding the approximate
solution of heart model based on nonlinear Van der Pol (VdP)-type second-order ordinary …

This work addresses the task of dense 3D reconstruction of a complex dynamic scene from
images. The prevailing idea to solve this task is composed of a sequence of steps and is …

In this paper we consider the problem of minimizing a smooth function by using the adaptive
cubic regularized (ARC) framework. We focus on the computation of the trial step as a …

Objective. We develop a model-based optimization algorithm for'one-step'dual-energy (DE)
CT decomposition of three materials directly from projection measurements. Approach …

This paper aims at the analysis of the VdP heartbeat mathematical model. We have
analysed the conditionality of a mathematical model which represents the oscillatory …

Quasi-Newton methods based on the symmetric rank-one (SR1) update have been known
to be fast and provide better approximations of the true Hessian than popular rank-two …

In this paper, two new subspace minimization conjugate gradient methods based on p-
regularization models are proposed, where a special scaled norm in p-regularization model …

In recent years, cubic regularization algorithms for unconstrained optimization have been
defined as alternatives to trust-region and line search schemes. These regularization …