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Distributions in the Physical and Engineering Sciences, Volume 1: Distributional and Fractal Calculus, Integral Transforms and Wavelets: Applied and Numerical Harmonic Analysis

Autor Alexander I. Saichev, Wojbor Woyczynski
en Limba Engleză Hardback – 11 sep 2018
Distributions in the Physical and Engineering Sciences is a comprehensive exposition on analytic methods for solving science and engineering problems which is written from the unifying viewpoint of distribution theory and enriched with many modern topics which are important to practitioners and researchers. The goal of the book is to give the reader, specialist and non-specialist usable and modern mathematical tools in their research and analysis. This new text is intended for graduate students and researchers in applied mathematics, physical sciences and engineering. The careful explanations, accessible writing style, and many illustrations/examples also make it suitable for use as a self-study reference by anyone seeking greater understanding and proficiency in the problem solving methods presented. The book is ideal for a general scientific and engineering audience, yet it is mathematically precise. The present, softcover reprint is designed to make this classic textbookavailable to a wider audience.
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Specificații

ISBN-13: 9783319979571
ISBN-10: 3319979574
Pagini: 336
Ilustrații: XX, 336 p. 62 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.68 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Birkhäuser
Seria Applied and Numerical Harmonic Analysis

Locul publicării:Cham, Switzerland

Cuprins

I Distributions and their Basic Applications.- 1 Basic Definitions and Operations.- 2 Basic Applications: Rigorous and Pragmatic.- II Integral Transforms and Divergent Series.- 3 Fourier Transform.- 4 Asymptotics of Fourier Transforms.- 5 Stationary Phase and Related Method.- 6 Singular Integrals and Fractal Calculus.- 7 Uncertainty Principle and Wavelet Transforms.- 8 Summation of Divergent Series and Integrals.- A Answers and Solutions.- A.1 Chapter 1. Definitions and operations.- A.2 Chapter 2. Basic applications.- A.3 Chapter 3. Fourier transform.- A.4 Chapter 4. Asymptotics of Fourier transforms.- A.5 Chapter 5. Stationary phase and related methods.- A.6 Chapter 6. Singular integrals and fractal calculus.- A.7 Chapter 7. Uncertainty principle and wavelet transform.- A. 8 Chapter 8. Summation of divergent series and integrals.- B Bibliographical Notes.

Notă biografică

​Alexander I. Saichev was Professor of Mathematics at the Radio Physics Faculty of the Nizhny Novgorod University and a Professor in the Department of Management, Technology, and Economics at the Swiss Federal Institute of Technology.

Wojbor A. Woyczynski is Professor of Mathematics and Director of the Center for Stochastic and Chaotic Processes in Science and Technology at Case Western University.


Textul de pe ultima copertă

Distributions in the Physical and Engineering Sciences is a comprehensive exposition on analytic methods for solving science and engineering problems which is written from the unifying viewpoint of distribution theory and enriched with many modern topics which are important to practitioners and researchers. The goal of the book is to give the reader, specialist and non-specialist usable and modern mathematical tools in their research and analysis. This new text is intended for graduate students and researchers in applied mathematics, physical sciences and engineering. The careful explanations, accessible writing style, and many illustrations/examples also make it suitable for use as a self-study reference by anyone seeking greater understanding and proficiency in the problem solving methods presented. The book is ideal for a general scientific and engineering audience, yet it is mathematically precise. 

Caracteristici

Illustrates how the theory of distributions can be applied to solve problems in the physical and engineering sciences Includes a robust selection of example problems that can arise in real-life industrial and scientific labs Will be a valuable resource for researchers and graduate students who would like more exposure to probabilistic methods