Convergence of a generalized method of conjugate gradients for the determination of the extremal eigenvalues of a matrix

For the determination of the minimal eigenvalue of a symmetric positive-definite matrix one obtains an estimate of the asymptotic rate of convergence of a generalized method of conjugate gradients, based on the method of the symmetric upper relaxation. One establishes the asymptotic value of the relaxation parameter.