Results 11 to 20 of about 32,780 (121)

Statistical convergence and ideal convergence for sequences of functions

Journal of Mathematical Analysis and Applications, 2007
The paper discusses various types of statistical convergence and ideal convergence for sequences of functions with real values or with values in a more general metric space. The authors present very thoroughly the definitions and types of ideal convergence for functions and prove several results regarding ideal pointwise and ideal uniform convergence ...
Balcerzak, Marek, Dems, Katarzyna, Komisarski, Andrzej   +2 more
openaire   +1 more source

Some Results on Quasi Ideal Statistical Convergence via Fuzzy Cone Normed Spaces [PDF]

Sahand Communications in Mathematical Analysis
In this paper, we have presented and explored the study of quasi ideal statistical convergence for sequences on fuzzy cone normed space.  The related topological and geometrical properties are illustrated with examples.
Reena Antal, Manpreet Kaur, Meenakshi Chawla   +2 more
doaj   +1 more source

Identification and Analysis of Influential Factors in Good Rural Governance (Case Study: Ardabil County) [PDF]

برنامه ریزی فضایی, 2022
Problem definition: Rural governance is a new process in the rural management system, which has different principles, criteria, and indicators, as well as many players in the rural field.Purpose: The present study was conducted with the aim of ...
Kiumarth Khodapanah
doaj   +1 more source

On Generalized Difference Rough Ideal Statistical Convergence in Neutrosophic Normed Spaces [PDF]

Neutrosophic Sets and Systems
This article’s main goal is to provide and investigate a novel statistical convergence generalisation for generalized difference sequences in Neutrosophic Normed Spaces (NNS) called rough ideal statistical convergence.
Manpreet Kaur, Meenakshi Chawla
doaj   +1 more source

On relation between statistical ideal and ideal generated by a modulus function

Visnik Harkivsʹkogo Nacionalʹnogo Universitetu im. V.N. Karazina. Cepiâ Matematika, Prikladna Matematika i Mehanika, 2022
Ideal on an arbitrary non-empty set $\Omega$ it's a non-empty family of subset $\mathfrak{I}$ of the set $\Omega$ which satisfies the following axioms: $\Omega \notin \mathfrak{I}$, if $A, B \in \mathfrak{I}$, then $A \cup B \in \mathfrak{I}$, if $A \in \
D. Seliutin
doaj   +1 more source

Ideal convergence generated by double summability methods

Demonstratio Mathematica, 2016
The main result of this note is that if I is an ideal generated by a regular double summability matrix summability method T that is the product of two nonnegative regular matrix methods for single sequences, then I-statistical convergence and convergence
Connor Jeff
doaj   +1 more source

Investigating the effect of social media marketing on brand loyalty with the mediating role of trust and brand equity(Case study: Bank Mellat Isfahan branches) [PDF]

ارزش آفرینی در مدیریت کسب و کار, 2022
The purpose of the present research is to investigate the impact of social media marketing on brand loyalty with the mediating role of trust and equity of the brand in Isfahan Bank Mellat branches.
Zahra Yazdani Kachuei, mehdi korhani, Asghar kosari   +2 more
doaj   +1 more source

Improving Bundle Routing in a Space DTN by Approximating the Transmission Time of the Reliable LTP

Network, 2023
Because the operation of space networks is carefully planned, it is possible to predict future contact opportunities from link budget analysis using the anticipated positions of the nodes over time.
Ricardo Lent
doaj   +1 more source

On deferred I-statistical rough convergence of difference sequences in neutrosophic normed spaces [PDF]

Neutrosophic Sets and Systems
In this study, using the concepts of deferred density and the notion of the ideal I, we extend the idea of rough convergence by introducing the notion of deferred I–statistical rough convergence via difference operators in the framework of neutrosophic ...
Mukhtar Ahmad, Ekrem Savas, Mohammad Mursaleen   +2 more
doaj   +1 more source

Experimental Evaluation and Analysis of Federated Learning in Edge Computing Environments

IEEE Access, 2023
Federated learning (FL) is a machine learning system that allows a network of devices to train a model without centralized data. This characteristic makes FL an ideal choice for machine learning using user data while maintaining privacy.
Pham Khanh Quan, Majid Kundroo, Taehong Kim   +2 more
doaj   +1 more source