English

On The Strong Convergence of The Gradient Projection Algorithm with Tikhonov regularizing term

Optimization and Control 2019-10-18 v1

Abstract

We investigate the strong and the weak convergence properties of the following gradient projection algorithm with Tikhonov regularizing term xn+1=PQ(xnγnf(xn)γnαnϕ(xn)), x_{n+1}=P_{Q}(x_{n}-\gamma_{n}\nabla f(x_{n})-\gamma_{n}\alpha_{n}\nabla \phi (x_{n})), where PQP_{Q} is the projection operator from a Hilbert space H\mathcal{H} onto a given nonempty, closed and convex subset Q,Q, f:Hf:\mathcal{H}% \rightarrow \mathbb{R} a regular convex function, ϕ:H\phi :\mathcal{H}% \rightarrow \mathbb{R} a regular strongly convex function, and γn\gamma_{n} and αn\alpha_{n} 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 (xn)n(x_{n})_{n} to a particular minimizer xx^{\ast } of ff on QQ under some simple and natural conditions on the objective function ff\ and the sequences (γn)n(\gamma_{n})_{n} and (αn)n(\alpha_{n})_{n}

Keywords

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

R2 v1 2026-06-23T11:46:38.085Z