Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Application of Linearization and Approximation01:29

Application of Linearization and Approximation

103
A drone flying through complex terrain often relies on more than one sensing method to estimate small changes in altitude. Along with direct measurements, air pressure provides a useful indirect indicator of vertical movement. Atmospheric pressure decreases as altitude increases, and this relationship is commonly described using an exponential model. Although accurate, converting pressure measurements into altitude values requires calculations that are too complex to perform repeatedly during...
103
Chemical Formulas02:52

Chemical Formulas

61.8K
A chemical formula presents information about the proportions of atoms constituting a particular chemical compound or molecule, mainly using symbols of elements and numbers. At times other symbols, such as dashes, parentheses, brackets, commas, plus, and minus signs, are also used. A chemical formula can be one of three types – molecular, empirical, and structural.
61.8K
Experimental Determination of Chemical Formula02:37

Experimental Determination of Chemical Formula

47.7K
The elemental makeup of a compound defines its chemical identity, and chemical formulas are the most concise way of representing this elemental makeup. When a compound’s formula is unknown, measuring the mass of its constituent elements is often the first step in determining the formula experimentally.
47.7K
Ionic Compounds: Formulas and Nomenclature03:34

Ionic Compounds: Formulas and Nomenclature

88.1K
An element composed of atoms that readily lose electrons (a metal) can react with an element composed of atoms that readily gain electrons (a nonmetal) to produce ions through complete electron transfer. The compound formed by this transfer is stabilized by the electrostatic attractions (ionic bonds) between the oppositely charged ions.
88.1K
Statistical Significance01:50

Statistical Significance

22.2K
Once data is collected from both the experimental and the control groups, a statistical analysis is conducted to find out if there are meaningful differences between the two groups. A statistical analysis determines how likely any difference found is due to chance (and thus not meaningful). In psychology, group differences are considered meaningful, or significant, if the odds that these differences occurred by chance alone are 5 percent or less. Stated another way, if we repeated this...
22.2K
Molecular Compounds: Formulas and Nomenclature03:10

Molecular Compounds: Formulas and Nomenclature

56.2K
Molecular compounds or covalent compounds result when atoms share electrons to form covalent bonds. Since there is no electron transfer, molecular compounds do not contain ions; instead, they consist of discrete, neutral molecules. 
56.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Extensive Surgical Emphysema in a Child after Primary Closure of Tracheocutaneous Fistula.

Case reports in anesthesiology·2020
Same author

CAN WE IMPROVE DETECTION OF BORDERLINE OVARIAN TUMORS?: IGCS-0065 Ovarian Cancer.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society·2015
Same author

THE SIGNIFICANCE OF PRE-OPERATIVE ENDOMETRIAL SAMPLING IN GRADE 1, LOW RISK ENDOMETRIAL CANCERS: IGCS-0088 Uterine Cancer, including Sarcoma.

International journal of gynecological cancer : official journal of the International Gynecological Cancer Society·2015
Same author

Droplet hydrodynamics during lysozyme protein crystallization.

Physical review. E, Statistical, nonlinear, and soft matter physics·2012
Same author

Melanotic neuroectodermal tumour of maxilla in infancy.

Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India·2012
Same author

Posterior cricoid split with costal cartilage augmentation for high subglottic stenosis.

Indian journal of otolaryngology and head and neck surgery : official publication of the Association of Otolaryngologists of India·2012

Related Experiment Video

Updated: Feb 12, 2026

Improving the Application of High Molecular Weight Biotinylated Dextran Amine for Thalamocortical Projection Tracing in the Rat
06:39

Improving the Application of High Molecular Weight Biotinylated Dextran Amine for Thalamocortical Projection Tracing in the Rat

Published on: April 12, 2018

9.5K

Statistical deferred weighted [Formula: see text]-summability and its applications to associated approximation

T Pradhan1, S K Paikray1, B B Jena1

  • 1Department of Mathematics, Veer Surendra Sai University of Technology, Sambalpur, India.

Journal of Inequalities and Applications
|April 3, 2018
PubMed
Summary

This study introduces statistical deferred weighted lambda-summability and deferred weighted lambda-statistical convergence. It establishes a new Korovkin-type approximation theorem and analyzes the convergence rate for functions in a Banach space.

Keywords:
Banach spaceDeferred weighted [Formula: see text]-statistical convergenceKorovkin-type approximation theoremsPositive linear operatorsRate of convergenceStatistical convergenceStatistical deferred weighted [Formula: see text]-summability

More Related Videos

Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition
07:42

Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition

Published on: September 3, 2016

15.5K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.1K

Related Experiment Videos

Last Updated: Feb 12, 2026

Improving the Application of High Molecular Weight Biotinylated Dextran Amine for Thalamocortical Projection Tracing in the Rat
06:39

Improving the Application of High Molecular Weight Biotinylated Dextran Amine for Thalamocortical Projection Tracing in the Rat

Published on: April 12, 2018

9.5K
Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition
07:42

Deferred Growth Inhibition Assay to Quantify the Effect of Bacteria-derived Antimicrobials on Competition

Published on: September 3, 2016

15.5K
Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms
08:51

Statistical Modelling of Cortical Connectivity Using Non-invasive Electroencephalograms

Published on: November 1, 2019

6.1K

Area of Science:

  • Mathematical Analysis
  • Approximation Theory
  • Functional Analysis

Background:

  • Introduces statistical weighted lambda-summability (Kadak et al., 2017).
  • Builds upon existing concepts in summability theory and approximation theorems.
  • Addresses the need for advanced convergence methods in functional analysis.

Purpose of the Study:

  • To investigate statistical deferred weighted lambda-summability and deferred weighted lambda-statistical convergence.
  • To establish an inclusion relation between these two novel convergence concepts.
  • To develop a new Korovkin-type approximation theorem for functions of two variables in a Banach space.

Main Methods:

  • Introduced and defined statistical deferred weighted lambda-summability and deferred weighted lambda-statistical convergence.
  • Established theoretical inclusion relations between the defined convergence types.
  • Utilized the modulus of continuity to analyze the rate of convergence.

Main Results:

  • Established a novel Korovkin-type approximation theorem for functions of two variables in a Banach space.
  • Demonstrated that the new theorem is a significant extension of existing approximation theorems.
  • Derived a result concerning the rate of deferred weighted lambda-statistical convergence.

Conclusions:

  • The study successfully introduced and analyzed new concepts in summability theory.
  • The developed Korovkin-type theorem offers a generalized approach to function approximation.
  • The findings provide a valuable contribution to the field of approximation theory and functional analysis.