Minimum residual norm iterative methods for solving linear systems Ax = b can be viewed as, and are often implemented as, sequences of least squares problems involving Krylov subspaces of increasing dimensions. The minimum residual method (MINRES) [C. Paige and M. Saunders, SIAM J. Numer. Anal., 12 (1975), pp. 617–629] and generalized minimum residual method (GMRES) [Y. Saad and M. Schultz, SIA...

fuzzy linear regression models are used to obtain an appropriate linear relation between a dependent variable and several independent variables in a fuzzy environment. several methods for evaluating fuzzy coefficients in linear regression models have been proposed. the first attempts at estimating the parameters of a fuzzy regression model used mathematical programming methods. in this the...

• Regression procedures are often used for estimating distributional parameters because of their computational simplicity and useful graphical presentation. However, the resulting regression model may have heteroscedasticity and/or correction problems and thus, weighted least squares estimation or alternative estimation methods should be used. In this study, we consider generalized least square...

This paper addresses the source location problem by using time-difference-of-arrival (TDOA) measurements. The two-stage weighted least squares (TWLS) algorithm has been widely used in TDOA location. However, estimation accuracy of is poor and bias significant when measurement noise large. Owing to nonlinear nature system model, we reformulate localization as a constrained derive theoretical est...