Approximations of Set-Valued Functions by Metric Linear Operators

نویسندگان

  • Nira Dyn
  • Elza Farkhi
  • Alona Mokhov
چکیده

In this work, we introduce new approximation operators for univariate setvalued functions with general compact images. We adapt linear approximation methods for real-valued functions by replacing linear combinations of numbers with new metric linear combinations of finite sequences of compact sets, thus obtaining ”metric analogues” operators for set-valued functions. The new metric linear combination extends the binary metric average of Artstein. Approximation estimates for the metric analogue operators are derived. As examples we study metric Bernstein operators, metric Shoenberg operators and metric polynomial interpolants.

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تاریخ انتشار 2005