On The Strong Convergence of The Gradient Projection Algorithm with Tikhonov regularizing term
Abstract
We investigate the strong and the weak convergence properties of the following gradient projection algorithm with Tikhonov regularizing term where is the projection operator from a Hilbert space onto a given nonempty, closed and convex subset a regular convex function, a regular strongly convex function, and and are positive real numbers. Following a Lyuapunov approach inspired essentially from the paper [Comminetti R, Peypouquet J Sorin S. Strong asymptotic convergence of evolution equations governed by maximal monotone operators with Tikhonov regularization. J. Differential Equations. (2001); 245:3753-3763], we establish the strong convergence of to a particular minimizer of on under some simple and natural conditions on the objective function \ and the sequences and
Cite
@article{arxiv.1910.07873,
title = {On The Strong Convergence of The Gradient Projection Algorithm with Tikhonov regularizing term},
author = {Ramzi May},
journal= {arXiv preprint arXiv:1910.07873},
year = {2019}
}
Comments
11 pages