ABSTRACT Let H be a real Hilbert space and K a nonempty, closed convex subset of H.Let T : K → K be Lipschitz pseudo-contractive map with a nonempty fixed points set. We introduce a modified Ishikawa iterative algorithm for Lipschitz pseudo-contractive maps and prove that our new iterative algorithm converges strongly to a fixed point of T in real Hilbert space.
Contents
Certification ii
Dedication iii
Acknowledgement iv
Abstract viii
1 Introduction 1
1.1 General Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Demiclosedness Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Nonlinear Mappings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Iterative Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.4.1 The Picard iteration Method . . . . . . . . . . . . . . . . . . . . . . 12
1.4.2 Krasnoselskii Iteration Method [6] . . . . . . . . . . . . . . . . . . . 13
1.4.3 The Mann Iteration Process [21] . . . . . . . . . . . . . . . . . . . . 14
1.4.4 The Ishikawa Iteration Process [19] . . . . . . . . . . . . . . . . . . 18
1.4.5 Mann Iteration Process with Errors in the Sense of Liu . . . . . . . 19
1.4.6 Ishikawa Iteration Process with Errors in the Sense of Liu . . . . . 19
vi
1.4.7 The Agarwal-O’Regan-Sahu Iteration Process . . . . . . . . . . . . 20
1.5 ORGANIZATION OF THESIS . . . . . . . . . . . . . . . . . . . . . . . . 21
2 Preliminaries 22
2.1 Definitions and Technical Results About Convergent Sequences of Real
Numbers. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
2.1.1 Definition (Strong Convergence) . . . . . . . . . . . . . . . . . . . . 22
2.1.2 Definition (Weak Convergence) . . . . . . . . . . . . . . . . . . . . 22
2.2 Projections onto Convex Set . . . . . . . . . . . . . . . . . . . . . . . . . . 33
2.3 Some Definitions and Results Used in the Main Work . . . . . . . . . . . . 36
2.4 Corollary (Demiclosedness Principle) . . . . . . . . . . . . . . . . . . . . . 38
3 Weak and Strong Convergence of an Iterative Algorithm for Lipschitz
Pseudo-Contractive Maps in Hilbert Spaces 44
3.1 Main Result . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
References 52
VELUHAN, E (2022). Weak and Strong Convergence of an Iterative Algorithm for Lipschitz Pseudo-Contractive Maps in Hilbert Spaces. Afribary. Retrieved from https://afribary.com/works/weak-and-strong-convergence-of-an-iterative-algorithm-for-lipschitz-pseudo-contractive-maps-in-hilbert-spaces
VELUHAN, EZEKIEL "Weak and Strong Convergence of an Iterative Algorithm for Lipschitz Pseudo-Contractive Maps in Hilbert Spaces" Afribary. Afribary, 18 Oct. 2022, https://afribary.com/works/weak-and-strong-convergence-of-an-iterative-algorithm-for-lipschitz-pseudo-contractive-maps-in-hilbert-spaces. Accessed 26 Nov. 2024.
VELUHAN, EZEKIEL . "Weak and Strong Convergence of an Iterative Algorithm for Lipschitz Pseudo-Contractive Maps in Hilbert Spaces". Afribary, Afribary, 18 Oct. 2022. Web. 26 Nov. 2024. < https://afribary.com/works/weak-and-strong-convergence-of-an-iterative-algorithm-for-lipschitz-pseudo-contractive-maps-in-hilbert-spaces >.
VELUHAN, EZEKIEL . "Weak and Strong Convergence of an Iterative Algorithm for Lipschitz Pseudo-Contractive Maps in Hilbert Spaces" Afribary (2022). Accessed November 26, 2024. https://afribary.com/works/weak-and-strong-convergence-of-an-iterative-algorithm-for-lipschitz-pseudo-contractive-maps-in-hilbert-spaces