PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 29, 2026Filomat1 citationsOpen Access

Approximation and convergence analysis of blending-type q-Baskakov operators using wavelet transformations

MAMohammad Ayman-Mursaleen

Key Points

  • This research aims to develop a new class of blending-type operators by combining q-Baskakov operators with wavelet transformations to enhance approximation properties.
  • Defined a family of blending-type operators using q-Baskakov and wavelet-based approximations.
  • Analyzed convergence in Lp and C[0,1] spaces, providing detailed error estimates and smoothness properties.
  • Provided numerical examples to demonstrate the application and accuracy of the proposed operators.
  • Established convergence rates and modulus of continuity of the blending-type q-Baskakov operators.
  • Demonstrated improved approximation accuracy in signal and function approximation scenarios.

Abstract

This paper introduces a new class of blending-type operators constructed by integrating the q-Baskakov operators with wavelet-based approximations. Utilising the Kantorovich modification, we define a family of operators that allows for effective control over approximation properties while enabling smooth blending through wavelet scaling functions. Our analysis focuses on the convergence behaviour of these operators in both Lp and C0,1 spaces, providing detailed error estimates and smoothness properties. We establish the modulus of continuity and convergence rates, highlighting the advantages of the blending-type approach in approximation theory. Numerical examples are provided to illustrate the practical application and accuracy of the proposed operators, particularly in signal and function approximation scenarios.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Mohammad Ayman-Mursaleen (2025) studied this question.

synapsesocial.com/papers/6a192eb9fab5b468c4418023https://doi.org/10.2298/fil2531117a
Ask AI
Helpful
Bookmark
Share
View Full Paper