Mean sampling Kantorovich operators: approximation results and applications
Abstract
Abstract As well-known, generalized sampling operators and sampling Kantorovich operators are able to approximate continuous signals and even $$L^p$$ L p -signals in the latter case. Anyway, in the situation of a signal affected by noise, these operators are not very efficient to approximate the original signal (i.e., filtered by the noise) when the parameter goes to infinity. In order to solve this problem, we introduce a new type of operators, which we call the mean sampling Kantorovich operators. We study its approximation properties and made a comparison with the classical sampling Kantorovich operator in dealing with noisy signals.
Fields of Study & Subjects
Approximation Theory and Sequence Spaces
Mathematical Analysis and Transform Methods
Neural Networks and Applications
Publication details
- Journal / source
- Revista de la Real Academia de Ciencias Exactas Físicas y Naturales Serie A Matemáticas
- Publisher
- Springer Science and Business Media LLC
- Volume
- 120
- Issue
- 2
- Publication date
- 27 January 2026
- Language
- EN