T. Tanushri
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
T. Tanushri has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Ayaz Ahmad
Department of Mathematics and Computing Technology, National Institute of Technology Patna, Patna, India
2 shared publications - Ayhan Esi
Malatya Turgut Ozal Universitesi
2 shared publications - Mohammad Mursaleen
Department of Mathematics, Bartin University, Bartin, Turkey
1 shared publication - Sk Ashadul Rahaman
Department of Mathematics, School of Advanced Sciences, VIT-AP University, Amaravati, India
1 shared publication
Latest Publications
- 24 December 2025
- Published by Springer Nature in Acta Mathematica Hungarica
- Vol. 177 (2) , 395-418
On $\mu$-sliding window statistical convergence of generalized fractional difference sequences in intuitionistic fuzzy normed spaces- 24 December 2025
- Published by Springer Nature in Acta Mathematica Hungarica
- Vol. 177 (2) , 395-418
On $\mu$-sliding window statistical convergence of generalized fractional difference sequences in intuitionistic fuzzy normed spaces- Open Access
A Framework for I*-Statistical Convergence of Fuzzy Numbers
In this study, we investigate the concept of -statistical convergence for sequences of fuzzy numbers. We establish several theorems that provide a comprehensive understanding of this notion, including the uniqueness of limits, the relationship between -statistical convergence and classical convergence, and the algebraic properties of -statistically convergent sequences. We also introduce the concept of -statistical pre-Cauchy and -statistical Cauchy sequences and explore its connection to -statistical convergence. Our results show that every -statistically convergent sequence is -statistically pre-Cauchy, but the converse is not necessarily true. Furthermore, we provide a sufficient condition for an -statistically pre-Cauchy sequence to be -statistically convergent, which involves the concept of .Open AccessA Framework for I*-Statistical Convergence of Fuzzy Numbers
In this study, we investigate the concept of -statistical convergence for sequences of fuzzy numbers. We establish several theorems that provide a comprehensive understanding of this notion, including the uniqueness of limits, the relationship between -statistical convergence and classical convergence, and the algebraic properties of -statistically convergent sequences. We also introduce the concept of -statistical pre-Cauchy and -statistical Cauchy sequences and explore its connection to -statistical convergence. Our results show that every -statistically convergent sequence is -statistically pre-Cauchy, but the converse is not necessarily true. Furthermore, we provide a sufficient condition for an -statistically pre-Cauchy sequence to be -statistically convergent, which involves the concept of . - Open Access
- 1 January 2024
- Published by National Library of Serbia in Filomat
- Vol. 38 (28) , 9769-9777
Monotonicity, boundedness, and convergence for sequences of fuzzy numbers
We present the concepts of ideal monotonicity and ideal boundedness in the context of sequences involving fuzzy numbers. Additionally, we formulate an equivalent to the monotone convergence theorem and provide the necessary proofs for decomposition theorems specifically designed for this category of sequences. Our exploration extends to the analysis of I*-convergent sequences of fuzzy numbers, concluding with the demonstration that these sequences have a unique limit point.
- 1 January 2024
- Published by National Library of Serbia in Filomat
- Vol. 38 (28) , 9769-9777
Open AccessMonotonicity, boundedness, and convergence for sequences of fuzzy numbers
We present the concepts of ideal monotonicity and ideal boundedness in the context of sequences involving fuzzy numbers. Additionally, we formulate an equivalent to the monotone convergence theorem and provide the necessary proofs for decomposition theorems specifically designed for this category of sequences. Our exploration extends to the analysis of I*-convergent sequences of fuzzy numbers, concluding with the demonstration that these sequences have a unique limit point.