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Panyanak also modified the iteration scheme of Sastry and Babu and posed the question of convergence of this scheme.
Using Lemma 1, Song and Wang [5] modified the iteration process due to Panyanak [4] and improved the results therein.
Based on the above Lemma, Song and Wang [7] modified the iteration scheme due to Panyanak [6] and improved the results presented therein.
Later, Eslamian and Abkar [47] generalized and modified the iteration of Abbas et al. [48] from two mappings to the infinite family of multivalued mappings { T i } such that each P T i satisfies the condition (C).
He also pointed out that the conditions lim n → ∞ α n = 0 and ∑ n = 1 ∞ α n = ∞ are necessary for the strong convergence of { x n } to a fixed point of T. Many authors have modified the iteration (1.6) for a strong convergence theorem; see, for instance, [8 10].
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The proposed method utilizes the parametric division algorithm to optimize the sensitivity measurement, then modifies the iteration algorithm and constructs the translational iteration algorithm to accelerate gain compression point measurement, and finally achieves the quick measurement of linear dynamic range.
Takahashi et al. [8] modified the Mann iteration method (1.4) and introduced the following hybrid projection algorithm: (1.5).
Recently, Su and Qin [6] modified the hybrid iteration method of Nakajo and Takahashi through the monotone hybrid method, and to prove strong convergence theorems.
Some attempts to modify the Mann iteration method so that strong convergence is guaranteed have recently been made (we should recall that Mann iteration method only guarantees weak convergence (see, for example, Bauschke et al. [20])).
Some attempts to modify the Mann iteration method (1.2) so that strong convergence is guaranteed have recently been made.
Attempts to modify the Mann iteration method (1.14) so that strong convergence is guaranteed have recently been made.
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