Global Krylov subspace methods are the most efficient and robust methods to solve generalized coupled Sylvester matrix equation. In this paper, we propose the nested splitting conjugate gradient process for solving this equation. This method has inner and outer iterations, which employs the generalized conjugate gradient method as an inner iteration to approximate each outer iterate, while each...

Traditional performance optimization techniques have focused on nding the kernel in a program that is the most time consuming and attempting to optimize it. We introduce a methodology for measuring and representing the interaction, or coupling, between kernels that improves upon the accuracy of the traditional method. Then we demonstrate the beneets of using the new methodology by developing a ...

Abstract: The existing literature predominantly concentrates on the utilization of the gradient descent algorithm for control systems’ design in power systems for stability enhancement. In this paper, various flavors of the Conjugate Gradient (CG) algorithm have been employed to design the online neuro-fuzzy linearization-based adaptive control strategy for Line Commutated Converters’ (LCC) Hig...

We discuss the implementation of a Sheikholeslami-Wohlert term for simulations of lattice QCD with dynamical Wilson fermions as required by Symanzik’s improvement program. We show that for the Hybrid Monte Carlo or Kramers equation algorithm standard even-odd preconditioning can be maintained. We design tests of the implementation using analytically and numerically computed cumulant expansions....

This Paper focused on adaptive conjugate gradient method (CGM) algorithm and the same is compared with one of the fastest adaptive algorithm named recursive least squares (RLS) algorithm. This algorithms has improved the computation complexity and better convergence. MATLAB simulation showed that conjugate gradient algorithm has better output signal resolution.

We compare the performance of several robust large-scale minimization algorithms applied for the minimization of the cost functional in the solution of ill-posed inverse problems related to parameter estimation applied to the parabolized Navier-Stokes equations. The methods compared consist of the conjugate gradient method (CG), Quasi-Newton (BFGS), the limited memory Quasi-Newton (L-BFGS) [1],...

In this paper we present a hybrid path-following algorithm that generates inexact Newton steps suited for solving large scale and/or degenerate nonlinear programs. The algorithm uses as a central region a relaxed notion of the central path, called quasicentral path, a generalized augmented Lagrangian function, weighted proximity measures, and a linesearch within a trust region strategy. We appl...

According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result. Keywords—Consensus protocols; Graph theory; Multi-agent systems; Conjugate gradient algorithm; Finite-time.