Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials (eBook)

Inequalities for polynomials and their derivatives are very important in many areas of mathematics, as well as in other computational and applied sciences; in particular they play a fundamental role in approximation theory. Here, not only Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials, but also ones for trigonometric polynomials and related functions, are treated in an integrated and comprehensive style in different metrics, both on general classes of polynomials and on important restrictive classes of polynomials. Primarily for graduate and PhD students, this book is useful for any researchers exploring problems which require derivative estimates. It is particularly useful for those studying inverse problems in approximation theory. - Applies Markov-Bernstein-type inequalities to any problem where derivative estimates are necessary - Presents complex math in a clean and simple way, progressing readers from polynomials into rational functions, and entire functions of exponential type - Contains exhaustive references with more than five hundred citations to articles and books - Features methods to solve inverse problems across approximation theory - Includes open problems for further research

Robert Gardner is a tenured Professor of Mathematics and Statistics at East Tennessee State University specializing in Bernstein-type inequalities. He has co-authored/co-edited two books, including Real Analysis with an Introduction to Wavelets and Applications that was published by Elsevier in 2005.

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Inequalities for polynomials and their derivatives are very important in many areas of mathematics, as well as in other computational and applied sciences; in particular they play a fundamental role in approximation theory. Here, not only Extremal Problems and Inequalities of Markov-Bernstein Type for Algebraic Polynomials, but also ones for trigonometric polynomials and related functions, are treated in an integrated and comprehensive style in different metrics, both on general classes of polynomials and on important restrictive classes of polynomials. Primarily for graduate and PhD students, this book is useful for any researchers exploring problems which require derivative estimates. It is particularly useful for those studying inverse problems in approximation theory. - Applies Markov-Bernstein-type inequalities to any problem where derivative estimates are necessary- Presents complex math in a clean and simple way, progressing readers from polynomials into rational functions, and entire functions of exponential type- Contains exhaustive references with more than five hundred citations to articles and books- Features methods to solve inverse problems across approximation theory- Includes open problems for further research