✨
AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
We prove that iterative algorithm (1.7) of [7] is weak $w^{2}-$stable w.r.t. an operator $T$ in the class of weak contraction mappings.
📌 3 Key Takeaways
🎯
Objective & Hypothesis:We prove that iterative algorithm (1.7) of [7] is weak $w^{2}-$stable w.r.t. an operator $T$ in the class of weak contraction mappings.
📊
Key Findings & Data:We prove that iterative algorithm (1.7) of [7] is weak $w^{2}-$stable w.r.t. an operator $T$ in the class of weak contraction mappings.
💡
Conclusion & Impact:We prove that iterative algorithm (1.7) of [7] is weak $w^{2}-$stable w.r.t. an operator $T$ in the class of weak contraction mappings.
🔬Design:Konferans Bildirisi
📍Scope:Comprehensive Sample
⚙️Variables:Fixed Point · Stability · Iterative algorithm
Abstract
We prove that iterative algorithm (1.7) of [7] is weak $w^{2}-$stable w.r.t. an operator $T$ in the class of weak contraction mappings.
🔖
Cite This Article
Gürsoy, F. (2019). Stability of an Iterative Algorithm. Conference Proceedings of Science and Technology, Cilt: 2 Sayı: 1, 18–19. https://ajindex.com/articles/1648748