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High Order Approximation by Sublinear and Max-Product Operators Using Convexity

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Nonlinearity: Ordinary and Fractional Approximations by Sublinear and Max-Product Operators

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 147))

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Abstract

Here we consider quantitatively using convexity the approximation of a function by general positive sublinear operators with applications to Max-product operators. These are of Bernstein type, of Favard–Szász–Mirakjan type, of Baskakov type, of Meyer–Köning and Zeller type, of sampling type, of Lagrange interpolation type and of Hermite–Fejér interpolation type. Our results are both: under the presence of smoothness and without any smoothness assumption on the function to be approximated which fulfills a convexity property. It follows Anastassiou (Approximation by Sublinear and Max-product Operators using Convexity, 2017, [6]).

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References

  1. G. Anastassiou, Moments in Probability and Approximation Theory, Pitman Research Notes in Mathematics Series (Longman Group UK, New York, 1993)

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  2. G. Anastassiou, Approximation by Sublinear Operators (2017, submitted)

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  3. G. Anastassiou, Approximation by Max-Product Operators (2017, submitted)

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  6. G. Anastassiou, Approximation by Sublinear and Max-product Operators Using Convexity (2017, submitted)

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Correspondence to George A. Anastassiou .

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Anastassiou, G.A. (2018). High Order Approximation by Sublinear and Max-Product Operators Using Convexity. In: Nonlinearity: Ordinary and Fractional Approximations by Sublinear and Max-Product Operators. Studies in Systems, Decision and Control, vol 147. Springer, Cham. https://doi.org/10.1007/978-3-319-89509-3_10

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  • DOI: https://doi.org/10.1007/978-3-319-89509-3_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-89508-6

  • Online ISBN: 978-3-319-89509-3

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