Approximation with Rates by Kantorovich–Choquet Quasi-interpolation Neural Network Operators

  • George A. AnastassiouEmail author
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 190)


In this chapter we present univariate and multivariate basic approximation by Kantorovich–Choquet type quasi-interpolation neural network operators with respect to supremum norm. This is done with rates using the first univariate and multivariate moduli of continuity. We approximate continuous and bounded functions on \(\mathbb {R}^{N},\) \(N\in \mathbb {N}\). When they are also uniformly continuous we have pointwise and uniform convergences. It follows [11].


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Mathematical SciencesUniversity of MemphisMemphisUSA

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