A linesearch (steplength) algorithm for unconstrained nonlinear least squares problems is described. To estimate the steplength inside the linesearch algorithm a new method that interpolates the residual vector is use...
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A linesearch (steplength) algorithm for unconstrained nonlinear least squares problems is described. To estimate the steplength inside the linesearch algorithm a new method that interpolates the residual vector is used together with a standards method that interpolates the sums of *** results are reported that point out the advantage with the new steplength estimation method.
Utilizing the Tikhonov regularization method and extragradient and linesearch methods, some new extragradient and linesearch algorithms have been introduced in the framework of Hilbert spaces. In the presented algorit...
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Utilizing the Tikhonov regularization method and extragradient and linesearch methods, some new extragradient and linesearch algorithms have been introduced in the framework of Hilbert spaces. In the presented algorithms, the convexity of optimization subproblems is assumed, which is weaker than the strong convexity assumption that is usually supposed in the literature, and also, the auxiliary equilibrium problem is not used. Some strong convergence theorems for the sequences generated by these algorithms have been proven. It has been shown that the limit point of the generated sequences is a common element of the solution set of an equilibrium problem and the solution set of a split feasibility problem in Hilbert spaces. To illustrate the usability of our results, some numerical examples are given. Optimization subproblems in these examples have been solved by FMINCON toolbox in MATLAB.
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