Solution of infinite linear systems by automatic adaptive iterations

Solution of Systems of Linear Equations by Minimized Iterations

In an earlier publication [14] a method was described which generated the eigenvalues and eigenvectors of a matrix by a successive algorithm based on minimizations by least squares. The advantage of this method consists in the fact that the successive iterations are constantly employed with maximum efficiency which guarantees fastest convergence for a given number of iterations. Moreover, with ...

Solution of Fully Fuzzy Linear Systems by ST Method

Minimal solution of fuzzy linear systems

In this paper, we use parametric form of fuzzy number and we converta fuzzy linear system to two linear system in crisp case. Conditions for the existence of a minimal solution to $mtimes n$ fuzzy linear equation systems are derived and a numerical procedure for calculating the minimal solution is designed. Numerical examples are presented to illustrate the proposed method.

Adaptive fuzzy pole placement for stabilization of non-linear systems

A new approach for pole placement of nonlinear systems using state feedback and fuzzy system is proposed. We use a new online fuzzy training method to identify and to obtain a fuzzy model for the unknown nonlinear system using only the system input and output. Then, we linearized this identified model at each sampling time to have an approximate linear time varying system. In order to stabilize...

Numerical stability of iterations for solution of nonlinear equations and large linear systems

We survey some recent results on the problem of numerical stability of iterations for the solution of nonlinear equations F(x) = 0 and large linear systems Ax+g = 0 where A = A is positive definite. For systems of nonlinear equations we assume that the function F depends on a so called data vector F(x) = F(x;d). We define the condition number cond(F;d), numerical stability and well-behavior of ...