Iterative solution of eigenvalue problems for normal operators
We will discuss Kellogg's iterations in eigenvalue problems for normal operators. A certain generalisation of the convergence theorem is shown.
Some functions of eigenvalues of normal operator
Kellogg's iterations in the eigenvalue problem are discussed with respect to the boundary spectrum of a linear normal operator.
On a certain class of always convergent sequences and the Rayleigh quotient iterations
An approximative solution of the generalized eigenvalue problem
A modification of a class of IAD methods
We provide a short overview of algorithms useful for computing of stationary probability vectors of stochastic matrix. Some care is devoted to the problem of computing of all extremal stationary probability vectors for the reducible stochastic matrices. We present some modifications of standard Iterative Aggregation/Disaggregation algorithm.
Page 1