Advertisement

Approximation Theorems

  • Ovidiu CalinEmail author
Chapter
  • 66 Downloads
Part of the Springer Series in the Data Sciences book series (SSDS)

Abstract

This chapter presents a few classical real analysis results with applications to learning continuous, integrable, or square-integrable functions. The approximation results included in this chapter contain Dini’s theorem, Arzela-Ascoli’s theorem, Stone-Weierstrass theorem, Wiener’s Tauberian theorem, and the contraction principle. Some of their applications to learning will be provided within this chapter, while others will be given in later chapters.

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Department of Mathematics & StatisticsEastern Michigan UniversityYpsilantiUSA

Personalised recommendations