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In this section, we establish an iterative method for finding the solution of hierarchical fixed point problem (1.1).
In this section, we propose and analyze an iterative method for finding the common solutions of EP (1.1) and HFPP (1.4).
In 1997, Combettes and Hirstoaga [9] introduced an iterative method for finding the best approximation to the initial data and proved a strong convergence theorem.
In 2008, Takahashi et al. [32] introduced an iterative method for finding the set of fixed point by Hybrid method in Hilbert spaces.
Recently Plubtieng and Punpaeng [7] introduced an iterative method for finding the common element of the set F ( T ) ∩ Ω ∗ ∩ E P ( F 1 ).
Ceng et al. [1] transformed problem (1.1) into a fixed-point problem (see Lemma 2.2) and introduced an iterative method for finding the common element of the set Fix ( T ) ∩ S ∗.
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Further, we propose an iterative method for finding a solution of the hierarchical variational inequality problem and prove the convergence result for the sequence generated by the proposed iterative method.
In this paper, based on the extragradient method, we introduce an iterative method for finding an element of the set of solutions of a variational inequality problem for a monotone and Lipschitz continuous mapping in Hilbert space.
In this paper, we suggested and analyzed an iterative method for finding an element of the common set of solutions of (1.1) and (1.4) in real Hilbert spaces.
The EM algorithm is an iterative method for finding maximum likelihood estimates of parameters in the presence of missing values or latent variables.
The purpose of this paper is to introduce an iterative method for finding solutions of a general system of variational inclusions with inverse-strongly accretive mappings.
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