Approximate Solutions Of Common Fixed-point Problems (springer Optimization And Its Applications)
by Alexander J. Zaslavski /
2016 / English / PDF
3.5 MB Download
This book presents results on the convergence behavior of
algorithms which are known as vital tools for solving convex
feasibility problems and common fixed point problems. The main
goal for us in dealing with a known computational error is to
find what approximate solution can be obtained and how many
iterates one needs to find it. According to know results, these
algorithms should converge to a solution. In this exposition,
these algorithms are studied, taking into account computational
errors which remain consistent in practice. In this case the
convergence to a solution does not take place. We show that our
algorithms generate a good approximate solution if computational
errors are bounded from above by a small positive constant.
This book presents results on the convergence behavior of
algorithms which are known as vital tools for solving convex
feasibility problems and common fixed point problems. The main
goal for us in dealing with a known computational error is to
find what approximate solution can be obtained and how many
iterates one needs to find it. According to know results, these
algorithms should converge to a solution. In this exposition,
these algorithms are studied, taking into account computational
errors which remain consistent in practice. In this case the
convergence to a solution does not take place. We show that our
algorithms generate a good approximate solution if computational
errors are bounded from above by a small positive constant.
Beginning with an introduction, this monograph moves on to
study:
Beginning with an introduction, this monograph moves on to
study:
· dynamic string-averaging methods for common fixed point
problems in a Hilbert space
· dynamic string-averaging methods for common fixed point
problems in a Hilbert space
· dynamic string methods for common fixed point problems in a
metric space<
· dynamic string methods for common fixed point problems in a metric space< · dynamic string-averaging version of the proximal algorithm
· dynamic string-averaging version of the proximal algorithm· common fixed point problems in metric spaces
· common fixed point problems in metric spaces · common fixed point problems in the spaces with distances of the Bregman type
· common fixed point problems in the spaces with distances of the Bregman type · a proximal algorithm for finding a common zero of a family of maximal monotone operators
· a proximal algorithm for finding a common zero of a family of maximal monotone operators · subgradient projections algorithms for convex feasibility problems in Hilbert spaces
· subgradient projections algorithms for convex feasibility problems in Hilbert spaces
