Applying the JII-SI, and CG methods to two classes of linear problems

Abstract

AbstractA Chebyshev semiiterative (JII-SI) method based on the optimum Jacobi second-degree iterative (JII) method is developed. A comparison of both methods and the conjugate gradient (CG) method is made by applying them to the two following classes of algebraic linear problems: systems with positive definite and consistently ordered matrix, and systems with positive definite and generalized stochastic matrix