An inertial forward–backward splitting method for solving combination of equilibrium problems and inclusion problems

An inertial forward-backward splitting method for approximating solutions of certain optimization problems

“…Remark 4.6. The iterative algorithm introduced in our article to approximate solutions of split general system of variational inequalities, minimization and fixed point problems of finite family of quasi-nonexpansive mapping yielded a strong convergence result which is desirable to the weak convergence result obtained in [16] and [26].…”

“…Furthermore, Khan, Cholamjiak and Kazmi [26] introduced the following inertial forwardbackward algorithm to approximate a common solution of the equilibrium problem, fixed points of an infinite family of nonexpansive mappings and the modified inclusion problem. For x 0 , x 1 ∈ H, let {x n }, {y n } and {u n } be sequences be generated by…”

“…Motivated by the ongoing interest on inertial-type algorithms and the results of Siriyan and Kangtunyakarn [15], Hieu [16], Cholamjiak, Pholasa and Suantai [25], Khan, Cholamjiak and Kazmi [26], Cheawchan and Kangtunyakarn [27], we introduce an inertial forward-backward splitting iterative algorithm for finding a common solution of a split general system of variational inequalities, the minimization problem and the fixed point problem of a finite family of quasi-nonexpansive mappings. We prove a strong convergence result in the framework of real Hilbert spaces and give some numerical examples for our main result.…”

An innovative inertial extra-proximal gradient algorithm for solving convex optimization problems with application to image and signal processing

“…The theory can be applied in variety of fields like machine learning, game theory, economics, control theory among others, see Refs. [ [1] , [2] , [3] , [4] , [5] , [6] , [7] , [8] , [9] , [10] ] for more details.…”

A modified parallel monotone hybrid algorithm for a finite family of $\mathcal{G}$-nonexpansive mappings apply to a novel signal recovery

“…Many mathematicians have used this algorithm (5) to modify in many ways such as the proximal point algorithm [13,21,25,28] and the gradient method [11,30,41,42]. For its applications, there have been modifications of the algorithm (5) in many various areas of science and physic etc., (see [7,8,10,16,17,23,26,44,36]).…”