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Frontiers in Approximation Theory

by Anastassiou George a

Approximation theory across several mathematical frameworks

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AlbakiReads Editorial

Approximation theory across several mathematical frameworks

Anastassiou brings together research on approximation theory spanning fractional differentiation, discrete singular operators, neural-network-induced interpolation, and analysis on time scales. The chapters are described as self-contained, allowing the topics to be approached independently. The book connects classical approximating tools such as polynomials and splines with newer frameworks, including neural networks, and places these subjects within both pure and applied mathematics. Its scope makes it a research-oriented monograph, with fractional approximation theory receiving particular attention.

Good fit for readers who enjoy

  • Researchers and graduate students working in approximation theory or functional analysis.
  • Instructors planning advanced courses or seminars on the book’s mathematical topics.
  • Science libraries seeking a research resource spanning several areas of approximation theory.

Themes

Fractional approximation theoryDiscrete singular operatorsNeural-network interpolationFunctional analysis on time scales

Based on publisher information and book metadata.

Book overview

 

This monograph presents the author's work of the last five years in approximation theory. The chapters are self-contained and can be read independently. Readers will find the topics covered are diverse and advanced courses can be taught out of this book.

The first part of the book is dedicated to fractional monotone approximation theory introduced for the first time by the author, taking the related ordinary theory of usual differentiation at the fractional differentiation level with polynomials and splines as approximators. The second part deals with the approximation by discrete singular operators of the Favard style, for example, of the Picard and Gauss-Weierstrass types. Then, it continues in a very detailed and extensive chapter on approximation by interpolating operators induced by neural networks, a connection to computer science. This book ends with the approximation theory and functional analysis on time scales, a very modern topic, detailing all the pros and cons of this method.

The results in this book are expected to find applications in many areas of pure and applied mathematics. So far, very little is written about fractional approximation theory which is at its infancy. As such, it is suitable for researchers, graduate students, and performing seminars as well as an invaluable resource for all science libraries.

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