Parallel synchronous algorithm for nonlinear fixed point problems.
Partial regularization of the sum of two maximal monotone operators
Perturbed Newton-like methods and nondifferentiable operator equations on Banach spaces with a convergence structure.
Perturbed three-step approximation process with errors for a generalized implicit nonlinear quasivariational inclusions.
Projection iterative schemes for general variational inequalities.
Projektive Newton-Verfahren und Anwendungen auf nichtlineare Randwertaufgaben.
Regular Splittings and Monotone Iteration Functions.
Regularization in state space
Regularization properties of Tikhonov regularization with sparsity constraints.
Relaxing convergence conditions for the Jarratt method.
Remark on a Newton-Moser type method
Remarks on inflated mappings
Résolution des équations semilinéaires avec la partie linéaire à noyau de dimension infinie via des applications A-propres [Book]
Results on controlling the residuals of perturbed Newton-like methods on Banach spaces with a convergence structure.
Selected papers from the 10th international conference 2009 on nonlinear functional analysis and applications, Seoul, Korea, July 27--31, 2009.
Semilocal analysis of equations with smooth operators.
Semilocal convergence for Newton's method on a Banach space with a convergence structure and twice Fréchet differentiable operators.
Sharp Error Bounds for Newton's Process.
Sharp upper global a posteriori error estimates for nonlinear elliptic variational problems
The paper is devoted to the problem of verification of accuracy of approximate solutions obtained in computer simulations. This problem is strongly related to a posteriori error estimates, giving computable bounds for computational errors and detecting zones in the solution domain where such errors are too large and certain mesh refinements should be performed. A mathematical model embracing nonlinear elliptic variational problems is considered in this work. Based on functional type estimates developed...
Signal reconstruction from given phase of the Fourier transform using Fejér monotone methods
The aim is to reconstruct a signal function x ∈ L₂ if the phase of the Fourier transform [x̂] and some additional a-priori information of convex type are known. The problem can be described as a convex feasibility problem. We solve this problem by different Fejér monotone iterative methods comparing the results and discussing the choice of relaxation parameters. Since the a-priori information is partly related to the spectral space the Fourier transform and its inverse have to be applied in each...