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Best approximation of (G(1), G(2))-random operator inequality in matrix Menger Banach algebras with application of stochastic Mittag-Leffler and H-Fox control functionsopen access

Authors
Rezaei Aderyani, SafouraSaadati, RezaRassias, Themistocles M.Park, Choonkil
Issue Date
Jan-2022
Publisher
SPRINGER
Keywords
Stochastic matrix control function; Mittag-Leffler; (G(1), G(2))-random operator inequality; Menger Banach algebra; H-Fox function
Citation
JOURNAL OF INEQUALITIES AND APPLICATIONS, v.2022, no.1, pp.1 - 17
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF INEQUALITIES AND APPLICATIONS
Volume
2022
Number
1
Start Page
1
End Page
17
URI
https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/138450
DOI
10.1186/s13660-021-02747-z
ISSN
1025-5834
Abstract
We stabilize pseudostochastic (G(1), G(2))-random operator inequality using a class of stochastic matrix control functions in matrix Menger Banach algebras. We get an approximation for stochastic (G(1), G(2))-random operator inequality by means of both direct and fixed point methods. As an application, we apply both stochastic Mittag-Leffler and H-fox control functions to get a better approximation in a random operator inequality.
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