Weighted statistical convergence through difference operator of sequences of fuzzy numbers with application to fuzzy approximation theorems

2019 ◽  
Vol 48 (5) ◽  
pp. 492-506 ◽  
Author(s):  
S. A. Mohiuddine ◽  
Asim Asiri ◽  
Bipan Hazarika
2020 ◽  
Vol 13 (5) ◽  
pp. 1212-1230
Author(s):  
Susanta Kumar Paikray ◽  
Priyadarsini Parida ◽  
S. A. Mohiuddine

The aim of this paper is to introduce the notions of relatively deferred Nörlund uniform statistical convergence as well as relatively deferred Norlund point-wise statistical convergence through the dierence operator of fractional order of fuzzy-number-valued sequence of functions, and a type of convergence which lies between aforesaid notions, namely, relatively deferred Nörlund equi-statistical convergence. Also, we investigate the inclusion relations among these aforesaidnotions. As an application point of view, we establish a fuzzy approximation (Korovkin-type) theorem by using our new notion of relatively deferred Norlund equi-statistical convergence and intimate that this result is a non-trivial generalization of several well-established fuzzy Korovkin-type theorems which were presented in earlier works. Moreover, we estimate the fuzzy rate of the relatively deferred Nörlund equi-statistical convergence involving a non-zero scale function by using the fuzzy modulus of continuity.


2015 ◽  
Vol 20 (9) ◽  
pp. 3611-3616 ◽  
Author(s):  
Abdulkadir Karakas ◽  
Yavuz Altin ◽  
Hifsi Altinok

2006 ◽  
Vol 02 (02) ◽  
pp. 123-130 ◽  
Author(s):  
EKREM SAVAŞ

In this paper, we study the space of almost convergent sequences of fuzzy numbers and show that it is complete metric space. We also introduce and discuss the concept of almost statistical convergence of fuzzy numbers.


Filomat ◽  
2019 ◽  
Vol 33 (9) ◽  
pp. 2683-2693 ◽  
Author(s):  
Özer Talo

In this paper, we define the concept of almost everywhere statistical convergence of a sequence of fuzzy numbers and prove that a sequence of fuzzy numbers is almost everywhere statistically convergent if and only if its statistical limit inferior and limit superior are equal. To achieve this result, new representations for statistical limit inferior and limit superior of a sequence of fuzzy numbers are obtained and we show that some properties of statistical limit inferior and limit superior can be easily derived from these representations.


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