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Rate of convergence of iterative sequences generated by the optimization algorithms is discussed.
The results are obtained using iterative sequences.
as, where,, and are iterative sequences generated by Algorithm 2.4.
(3) We obtain some estimating expression for the iterative sequences.
Next we consider the equivalence between some explicit iterative sequences.
Theorem 3.3 and Corollary 3.4 prove strong convergence results of the new iterative sequences which are different from the iterative sequences (1.4) and (1.5).
In this article, strong convergence of Krasnoselski-Mann iterative sequences and Halpern iterative sequences are investigated based on hybrid projection methods.
For any given, the iterative sequences and are defined by (3.8).
The iterative sequences,,,, and,, generated by Algorithm 3.3 converge strongly to,,,,,, respectively.
The iterative sequence (1.7) is a natural generalization of the Mann iterative sequences (1.6).
Moreover, we can approximate the positive solution or negative solution by constructing two iterative sequences.
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