Korovkin-type convergence results for non-positive operators
Autor: | Oliver Nowak |
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Rok vydání: | 2010 |
Předmět: |
multivariate scattered data interpolation
Discrete mathematics 41a05 General Mathematics Singular integral operators of convolution type moving least squares interpolation Spectral theorem Operator theory regular operator Fourier integral operator Quasinormal operator non-positive operator QA1-939 41a63 Moving least squares 41a36 positive operator Operator norm Mathematics korovkin-type approximation theory 41a35 Interpolation |
Zdroj: | Open Mathematics, Vol 8, Iss 5, Pp 890-907 (2010) |
ISSN: | 1644-3616 1895-1074 |
DOI: | 10.2478/s11533-010-0058-8 |
Popis: | Korovkin-type approximation theory usually deals with convergence analysis for sequences of positive operators. In this work we present qualitative Korovkin-type convergence results for a class of sequences of non-positive operators, more precisely regular operators with vanishing negative parts under a limiting process. Sequences of that type are called sequences of almost positive linear operators and have not been studied before in the context of Korovkin-type approximation theory. As an example we show that operators related to the multivariate scattered data interpolation technique moving least squares interpolation originally due to Lancaster and Salkauskas [Surfaces generated by moving least squares methods, Math. Comp., 1981, 37, 141–158] give rise to such sequences. This work also generalizes Korovkin-type results regarding Shepard interpolation [Korovkin-type convergence results for multivariate Shepard formulae, Rev. Anal. Numer. Theor. Approx., 2009, 38, 170–176] due to the author. Moreover, this work establishes connections and differences between the concepts of sequences of almost positive linear operators and sequences of quasi-positive or convexity-monotone linear operators introduced and studied by Campiti in [Convexity-monotone operators in Korovkin theory, Rend. Circ. Mat. Palermo (2) Suppl., 1993, 33, 229–238]. |
Databáze: | OpenAIRE |
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