Metrics Norms Inner Products And Operator Theory

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Metrics, Norms, Inner Products, and Operator Theory

Author : Christopher Heil
Publisher : Birkhäuser
Page : 359 pages
File Size : 43,5 Mb
Release : 2018-08-28
Category : Mathematics
ISBN : 9783319653228

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Metrics, Norms, Inner Products, and Operator Theory by Christopher Heil Pdf

This text is a self-contained introduction to the three main families that we encounter in analysis – metric spaces, normed spaces, and inner product spaces – and to the operators that transform objects in one into objects in another. With an emphasis on the fundamental properties defining the spaces, this book guides readers to a deeper understanding of analysis and an appreciation of the field as the “science of functions.” Many important topics that are rarely presented in an accessible way to undergraduate students are included, such as unconditional convergence of series, Schauder bases for Banach spaces, the dual of lp topological isomorphisms, the Spectral Theorem, the Baire Category Theorem, and the Uniform Boundedness Principle. The text is constructed in such a way that instructors have the option whether to include more advanced topics. Written in an appealing and accessible style, Metrics, Norms, Inner Products, and Operator Theory is suitable for independent study or as the basis for an undergraduate-level course. Instructors have several options for building a course around the text depending on the level and interests of their students. Key features: Aimed at students who have a basic knowledge of undergraduate real analysis. All of the required background material is reviewed in the first chapter. Suitable for undergraduate-level courses; no familiarity with measure theory is required. Extensive exercises complement the text and provide opportunities for learning by doing. A separate solutions manual is available for instructors via the Birkhäuser website (www.springer.com/978-3-319-65321-1). Unique text providing an undergraduate-level introduction to metrics, norms, inner products, and their associated operator theory.

Operator Theory in Inner Product Spaces

Author : Karl-Heinz Förster,Peter Jonas,Heinz Langer,Carsten Trunk
Publisher : Springer Science & Business Media
Page : 242 pages
File Size : 40,7 Mb
Release : 2007-03-20
Category : Mathematics
ISBN : 9783764382698

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Operator Theory in Inner Product Spaces by Karl-Heinz Förster,Peter Jonas,Heinz Langer,Carsten Trunk Pdf

This volume contains contributions written by participants of the 4th Workshop on Operator Theory in Krein Spaces and Applications, held at the TU Berlin, Germany, December 17 to 19, 2004. The workshop covered topics from spectral, perturbation, and extension theory of linear operators and relations in inner product spaces.

Sampling: Theory and Applications

Author : Stephen D. Casey,Kasso A. Okoudjou,Michael Robinson,Brian M. Sadler
Publisher : Springer Nature
Page : 210 pages
File Size : 49,7 Mb
Release : 2020-05-20
Category : Mathematics
ISBN : 9783030362911

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Sampling: Theory and Applications by Stephen D. Casey,Kasso A. Okoudjou,Michael Robinson,Brian M. Sadler Pdf

The chapters of this volume are based on talks given at the eleventh international Sampling Theory and Applications conference held in 2015 at American University in Washington, D.C. The papers highlight state-of-the-art advances and trends in sampling theory and related areas of application, such as signal and image processing. Chapters have been written by prominent mathematicians, applied scientists, and engineers with an expertise in sampling theory. Claude Shannon’s 100th birthday is also celebrated, including an introductory essay that highlights Shannon’s profound influence on the field. The topics covered include both theory and applications, such as: • Compressed sensing• Non-uniform and wave sampling• A-to-D conversion• Finite rate of innovation• Time-frequency analysis• Operator theory• Mobile sampling issues Sampling: Theory and Applications is ideal for mathematicians, engineers, and applied scientists working in sampling theory or related areas.

Theoretical Physics, Wavelets, Analysis, Genomics

Author : Patrick Flandrin,Stéphane Jaffard,Thierry Paul,Bruno Torresani
Publisher : Springer Nature
Page : 650 pages
File Size : 49,7 Mb
Release : 2023-05-31
Category : Mathematics
ISBN : 9783030458478

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Theoretical Physics, Wavelets, Analysis, Genomics by Patrick Flandrin,Stéphane Jaffard,Thierry Paul,Bruno Torresani Pdf

Over the course of a scientific career spanning more than fifty years, Alex Grossmann (1930-2019) made many important contributions to a wide range of areas including, among others, mathematics, numerical analysis, physics, genetics, and biology. His lasting influence can be seen not only in his research and numerous publications, but also through the relationships he cultivated with his collaborators and students. This edited volume features chapters written by some of these colleagues, as well as researchers whom Grossmann’s work and way of thinking has impacted in a decisive way. Reflecting the diversity of his interests and their interdisciplinary nature, these chapters explore a variety of current topics in quantum mechanics, elementary particles, and theoretical physics; wavelets and mathematical analysis; and genomics and biology. A scientific biography of Grossmann, along with a more personal biography written by his son, serve as an introduction. Also included are the introduction to his PhD thesis and an unpublished paper coauthored by him. Researchers working in any of the fields listed above will find this volume to be an insightful and informative work.

The XFT Quadrature in Discrete Fourier Analysis

Author : Rafael G. Campos
Publisher : Springer
Page : 235 pages
File Size : 42,9 Mb
Release : 2019-05-24
Category : Mathematics
ISBN : 9783030134235

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The XFT Quadrature in Discrete Fourier Analysis by Rafael G. Campos Pdf

This book has two main objectives, the first of which is to extend the power of numerical Fourier analysis and to show by means of theoretical examples and numerous concrete applications that when computing discrete Fourier transforms of periodic and non periodic functions, the usual kernel matrix of the Fourier transform, the discrete Fourier transform (DFT), should be replaced by another kernel matrix, the eXtended Fourier transform (XFT), since the XFT matrix appears as a convergent quadrature of a more general transform, the fractional Fourier transform. In turn, the book’s second goal is to present the XFT matrix as a finite-dimensional transformation that links certain discrete operators in the same way that the corresponding continuous operators are related by the Fourier transform, and to show that the XFT matrix accordingly generates sequences of matrix operators that represent continuum operators, and which allow these operators to be studied from another perspective.

Modulation Spaces

Author : Árpád Bényi,Kasso A. Okoudjou
Publisher : Springer Nature
Page : 177 pages
File Size : 53,7 Mb
Release : 2020-02-22
Category : Mathematics
ISBN : 9781071603321

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Modulation Spaces by Árpád Bényi,Kasso A. Okoudjou Pdf

This monograph serves as a much-needed, self-contained reference on the topic of modulation spaces. By gathering together state-of-the-art developments and previously unexplored applications, readers will be motivated to make effective use of this topic in future research. Because modulation spaces have historically only received a cursory treatment, this book will fill a gap in time-frequency analysis literature, and offer readers a convenient and timely resource. Foundational concepts and definitions in functional, harmonic, and real analysis are reviewed in the first chapter, which is then followed by introducing modulation spaces. The focus then expands to the many valuable applications of modulation spaces, such as linear and multilinear pseudodifferential operators, and dispersive partial differential equations. Because it is almost entirely self-contained, these insights will be accessible to a wide audience of interested readers. Modulation Spaces will be an ideal reference for researchers in time-frequency analysis and nonlinear partial differential equations. It will also appeal to graduate students and seasoned researchers who seek an introduction to the time-frequency analysis of nonlinear dispersive partial differential equations.

Topics in Classical and Modern Analysis

Author : Martha Abell,Emil Iacob,Alex Stokolos,Sharon Taylor,Sergey Tikhonov,Jiehua Zhu
Publisher : Springer Nature
Page : 373 pages
File Size : 41,7 Mb
Release : 2019-10-21
Category : Mathematics
ISBN : 9783030122775

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Topics in Classical and Modern Analysis by Martha Abell,Emil Iacob,Alex Stokolos,Sharon Taylor,Sergey Tikhonov,Jiehua Zhu Pdf

Different aspects of harmonic analysis, complex analysis, sampling theory, approximation theory and related topics are covered in this volume. The topics included are Fourier analysis, Padè approximation, dynamical systems and difference operators, splines, Christoffel functions, best approximation, discrepancy theory and Jackson-type theorems of approximation. The articles of this collection were originated from the International Conference in Approximation Theory, held in Savannah, GA in 2017, and organized by the editors of this volume.

Excursions in Harmonic Analysis, Volume 6

Author : Matthew Hirn,Shidong Li,Kasso A. Okoudjou,Sandra Saliani,Özgür Yilmaz
Publisher : Springer Nature
Page : 444 pages
File Size : 45,5 Mb
Release : 2021-09-01
Category : Mathematics
ISBN : 9783030696375

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Excursions in Harmonic Analysis, Volume 6 by Matthew Hirn,Shidong Li,Kasso A. Okoudjou,Sandra Saliani,Özgür Yilmaz Pdf

John J. Benedetto has had a profound influence not only on the direction of harmonic analysis and its applications, but also on the entire community of people involved in the field. The chapters in this volume – compiled on the occasion of his 80th birthday – are written by leading researchers in the field and pay tribute to John’s many significant and lasting achievements. Covering a wide range of topics in harmonic analysis and related areas, these chapters are organized into four main parts: harmonic analysis, wavelets and frames, sampling and signal processing, and compressed sensing and optimization. An introductory chapter also provides a brief overview of John’s life and mathematical career. This volume will be an excellent reference for graduate students, researchers, and professionals in pure and applied mathematics, engineering, and physics.

Introduction to Real Analysis

Author : Christopher Heil
Publisher : Springer
Page : 386 pages
File Size : 41,7 Mb
Release : 2019-07-20
Category : Mathematics
ISBN : 9783030269036

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Introduction to Real Analysis by Christopher Heil Pdf

Developed over years of classroom use, this textbook provides a clear and accessible approach to real analysis. This modern interpretation is based on the author’s lecture notes and has been meticulously tailored to motivate students and inspire readers to explore the material, and to continue exploring even after they have finished the book. The definitions, theorems, and proofs contained within are presented with mathematical rigor, but conveyed in an accessible manner and with language and motivation meant for students who have not taken a previous course on this subject. The text covers all of the topics essential for an introductory course, including Lebesgue measure, measurable functions, Lebesgue integrals, differentiation, absolute continuity, Banach and Hilbert spaces, and more. Throughout each chapter, challenging exercises are presented, and the end of each section includes additional problems. Such an inclusive approach creates an abundance of opportunities for readers to develop their understanding, and aids instructors as they plan their coursework. Additional resources are available online, including expanded chapters, enrichment exercises, a detailed course outline, and much more. Introduction to Real Analysis is intended for first-year graduate students taking a first course in real analysis, as well as for instructors seeking detailed lecture material with structure and accessibility in mind. Additionally, its content is appropriate for Ph.D. students in any scientific or engineering discipline who have taken a standard upper-level undergraduate real analysis course.

Machine Learning Meets Quantum Physics

Author : Kristof T. Schütt,Stefan Chmiela,O. Anatole von Lilienfeld,Alexandre Tkatchenko,Koji Tsuda,Klaus-Robert Müller
Publisher : Springer Nature
Page : 473 pages
File Size : 51,9 Mb
Release : 2020-06-03
Category : Science
ISBN : 9783030402457

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Machine Learning Meets Quantum Physics by Kristof T. Schütt,Stefan Chmiela,O. Anatole von Lilienfeld,Alexandre Tkatchenko,Koji Tsuda,Klaus-Robert Müller Pdf

Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.

Advances in Microlocal and Time-Frequency Analysis

Author : Paolo Boggiatto,Marco Cappiello,Elena Cordero,Sandro Coriasco,Gianluca Garello,Alessandro Oliaro,Jörg Seiler
Publisher : Springer Nature
Page : 533 pages
File Size : 50,9 Mb
Release : 2020-03-03
Category : Mathematics
ISBN : 9783030361389

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Advances in Microlocal and Time-Frequency Analysis by Paolo Boggiatto,Marco Cappiello,Elena Cordero,Sandro Coriasco,Gianluca Garello,Alessandro Oliaro,Jörg Seiler Pdf

The present volume gathers contributions to the conference Microlocal and Time-Frequency Analysis 2018 (MLTFA18), which was held at Torino University from the 2nd to the 6th of July 2018. The event was organized in honor of Professor Luigi Rodino on the occasion of his 70th birthday. The conference’s focus and the contents of the papers reflect Luigi’s various research interests in the course of his long and extremely prolific career at Torino University.

Compressed Sensing and Its Applications

Author : Holger Boche,Giuseppe Caire,Robert Calderbank,Gitta Kutyniok,Rudolf Mathar,Philipp Petersen
Publisher : Birkhäuser
Page : 305 pages
File Size : 50,6 Mb
Release : 2019-08-13
Category : Mathematics
ISBN : 9783319730745

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Compressed Sensing and Its Applications by Holger Boche,Giuseppe Caire,Robert Calderbank,Gitta Kutyniok,Rudolf Mathar,Philipp Petersen Pdf

The chapters in this volume highlight the state-of-the-art of compressed sensing and are based on talks given at the third international MATHEON conference on the same topic, held from December 4-8, 2017 at the Technical University in Berlin. In addition to methods in compressed sensing, chapters provide insights into cutting edge applications of deep learning in data science, highlighting the overlapping ideas and methods that connect the fields of compressed sensing and deep learning. Specific topics covered include: Quantized compressed sensing Classification Machine learning Oracle inequalities Non-convex optimization Image reconstruction Statistical learning theory This volume will be a valuable resource for graduate students and researchers in the areas of mathematics, computer science, and engineering, as well as other applied scientists exploring potential applications of compressed sensing.

Harmonic and Applied Analysis

Author : Filippo De Mari,Ernesto De Vito
Publisher : Springer Nature
Page : 316 pages
File Size : 50,5 Mb
Release : 2021-12-13
Category : Mathematics
ISBN : 9783030866648

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Harmonic and Applied Analysis by Filippo De Mari,Ernesto De Vito Pdf

Deep connections exist between harmonic and applied analysis and the diverse yet connected topics of machine learning, data analysis, and imaging science. This volume explores these rapidly growing areas and features contributions presented at the second and third editions of the Summer Schools on Applied Harmonic Analysis, held at the University of Genova in 2017 and 2019. Each chapter offers an introduction to essential material and then demonstrates connections to more advanced research, with the aim of providing an accessible entrance for students and researchers. Topics covered include ill-posed problems; concentration inequalities; regularization and large-scale machine learning; unitarization of the radon transform on symmetric spaces; and proximal gradient methods for machine learning and imaging.

Mathematical Image Processing

Author : Kristian Bredies,Dirk Lorenz
Publisher : Springer
Page : 473 pages
File Size : 45,7 Mb
Release : 2019-02-06
Category : Mathematics
ISBN : 9783030014582

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Mathematical Image Processing by Kristian Bredies,Dirk Lorenz Pdf

This book addresses the mathematical aspects of modern image processing methods, with a special emphasis on the underlying ideas and concepts. It discusses a range of modern mathematical methods used to accomplish basic imaging tasks such as denoising, deblurring, enhancing, edge detection and inpainting. In addition to elementary methods like point operations, linear and morphological methods, and methods based on multiscale representations, the book also covers more recent methods based on partial differential equations and variational methods. Review of the German Edition: The overwhelming impression of the book is that of a very professional presentation of an appropriately developed and motivated textbook for a course like an introduction to fundamentals and modern theory of mathematical image processing. Additionally, it belongs to the bookcase of any office where someone is doing research/application in image processing. It has the virtues of a good and handy reference manual. (zbMATH, reviewer: Carl H. Rohwer, Stellenbosch)

Framelets and Wavelets

Author : Bin Han
Publisher : Springer
Page : 750 pages
File Size : 47,7 Mb
Release : 2018-01-04
Category : Mathematics
ISBN : 9783319685304

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Framelets and Wavelets by Bin Han Pdf

Marking a distinct departure from the perspectives of frame theory and discrete transforms, this book provides a comprehensive mathematical and algorithmic introduction to wavelet theory. As such, it can be used as either a textbook or reference guide. As a textbook for graduate mathematics students and beginning researchers, it offers detailed information on the basic theory of framelets and wavelets, complemented by self-contained elementary proofs, illustrative examples/figures, and supplementary exercises. Further, as an advanced reference guide for experienced researchers and practitioners in mathematics, physics, and engineering, the book addresses in detail a wide range of basic and advanced topics (such as multiwavelets/multiframelets in Sobolev spaces and directional framelets) in wavelet theory, together with systematic mathematical analysis, concrete algorithms, and recent developments in and applications of framelets and wavelets. Lastly, the book can also be used to teach on or study selected special topics in approximation theory, Fourier analysis, applied harmonic analysis, functional analysis, and wavelet-based signal/image processing.