A Comprehensive Analysis of Stability and Data Dependency for a Novel Jungck-type Iterative Algorithm

Kapil Kumar *

Department of Mathematics, Baba Mastnath University, Asthal Bohar-124021, Rohtak, Haryana, India.

Vivek Kumar

Department of Mathematics, KLP College, Rewari-123401, Haryana, India.

Ranbir Singh

Department of Mathematics, Baba Mastnath University, Asthal Bohar-124021, Rohtak, Haryana, India.

Satish Narwal

Department of Mathematics, Sat Jinda Kalyana College, Kalanaur-124113, Rohtak, Haryana, India.

*Author to whom correspondence should be addressed.


Abstract

This study introduces a novel Jungck-type iterative algorithm for approximating coincidence points under specific contractive conditions. The research demonstrates the algorithm's strong convergence, stability, and data dependency through rigorous theoretical analysis and numerical experiments. Results indicate that the proposed method achieves a significantly faster convergence rate compared to existing Jungck-type iterations. These findings have practical implications in fields such as optimization, economic modeling, and coupled differential equations, where iterative techniques are vital.

Keywords: Data dependence, common fixed point, coincidence point, stability


How to Cite

Kumar, Kapil, Vivek Kumar, Ranbir Singh, and Satish Narwal. 2025. “A Comprehensive Analysis of Stability and Data Dependency for a Novel Jungck-Type Iterative Algorithm”. Journal of Advances in Mathematics and Computer Science 40 (1):107-21. https://doi.org/10.9734/jamcs/2025/v40i11965.

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