Cargando…
Towards Intelligent Modeling: Statistical Approximation Theory
The main idea of statistical convergence is to demand convergence only for a majority of elements of a sequence. This method of convergence has been investigated in many fundamental areas of mathematics such as: measure theory, approximation theory, fuzzy logic theory, summability theory, and so on....
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2011.
|
| Edición: | 1st ed. 2011. |
| Colección: | Intelligent Systems Reference Library,
14 |
| Temas: | |
| Acceso en línea: | Texto Completo |
Tabla de Contenidos:
- Introduction
- Statistical Approximation by Bivariate Picard Singular Integral Operators
- Uniform Approximation in Statistical Sense by Bivariate Gauss-Weierstrass Singular Integral Operators
- Statistical Lp-Convergence of Bivariate Smooth Picard Singular Integral Operators
- Statistical Lp-Approximation by Bivariate Gauss-Weierstrass Singular Integral Operators
- A Baskakov-Type Generalization of Statistical Approximation Theory
- Weighted Approximation in Statistical Sense to Derivatives of Functions
- Statistical Approximation to Periodic Functions by a General Family of Linear Operators
- Relaxing the Positivity Condition of Linear Operators in Statistical Korovkin Theory
- Statistical Approximation Theory for Stochastic Processes
- Statistical Approximation Theory for Multivariate Stochas tic Processes.