Statistical convergence and ideal convergence for sequences of functions
Copyright policy )Statistical convergence and ideal convergence for sequences of functions
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. The results are exemplified through analytical instances. The main outcomes of the paper are the derivation and proof of two theorems, counterparts of the Egorov and Riesz theorems from classical analysis, in which statistical convergence of measurable functions is used.
- University of Łódź Poland
- Polish Academy of Sciences Poland
- Uniwersity of Lodz Poland
- Uniwersytet Łódzki (University of Lodz) Poland
- Lodz University of Technology Poland
Equi-statistical convergence, I-Uniform convergence, Statistical Egorov's theorem, statistical Egorovs theorem, Applied Mathematics, Statistical convergence in measure, Convergence and divergence of series and sequences of functions, statistical convergence, ideal convergence, Analysis
Equi-statistical convergence, I-Uniform convergence, Statistical Egorov's theorem, statistical Egorovs theorem, Applied Mathematics, Statistical convergence in measure, Convergence and divergence of series and sequences of functions, statistical convergence, ideal convergence, Analysis
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).97 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 1% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
Citations provided by BIP!Popularity provided by BIP!