Mathematical Analysis and Applications

Author: Michael Ruzhansky
Publisher: John Wiley & Sons
ISBN: 9781119414308
Release Date: 2018-04-05
Genre: Mathematics

An authoritative text that presents the current problems, theories, and applications of mathematical analysis research Mathematical Analysis and Applications: Selected Topics offers the theories, methods, and applications of a variety of targeted topics including: operator theory, approximation theory, fixed point theory, stability theory, minimization problems, many-body wave scattering problems, Basel problem, Corona problem, inequalities, generalized normed spaces, variations of functions and sequences, analytic generalizations of the Catalan, Fuss, and Fuss–Catalan Numbers, asymptotically developable functions, convex functions, Gaussian processes, image analysis, and spectral analysis and spectral synthesis. The authors—a noted team of international researchers in the field— highlight the basic developments for each topic presented and explore the most recent advances made in their area of study. The text is presented in such a way that enables the reader to follow subsequent studies in a burgeoning field of research. This important text: Presents a wide-range of important topics having current research importance and interdisciplinary applications such as game theory, image processing, creation of materials with a desired refraction coefficient, etc. Contains chapters written by a group of esteemed researchers in mathematical analysis Includes problems and research questions in order to enhance understanding of the information provided Offers references that help readers advance to further study Written for researchers, graduate students, educators, and practitioners with an interest in mathematical analysis, Mathematical Analysis and Applications: Selected Topics includes the most recent research from a range of mathematical fields.

Hilbert Space Methods in Signal Processing

Author: Rodney A. Kennedy
Publisher: Cambridge University Press
ISBN: 9781107328358
Release Date: 2013-03-07
Genre: Technology & Engineering

This lively and accessible book describes the theory and applications of Hilbert spaces and also presents the history of the subject to reveal the ideas behind theorems and the human struggle that led to them. The authors begin by establishing the concept of 'countably infinite', which is central to the proper understanding of separable Hilbert spaces. Fundamental ideas such as convergence, completeness and dense sets are first demonstrated through simple familiar examples and then formalised. Having addressed fundamental topics in Hilbert spaces, the authors then go on to cover the theory of bounded, compact and integral operators at an advanced but accessible level. Finally, the theory is put into action, considering signal processing on the unit sphere, as well as reproducing kernel Hilbert spaces. The text is interspersed with historical comments about central figures in the development of the theory, which helps bring the subject to life.


ISBN: UCSC:32106018412426
Release Date: 2005
Genre: Artificial intelligence

Information Theory

Author: Sergio Verdú
Publisher: Wiley-IEEE Press
ISBN: 0780353633
Release Date: 2000
Genre: Technology & Engineering

Celebrating 50 years since the discovery of information theory by Claude Shannon, this book consists to the 50 best tutorials in the area compiled by the editors of the "IEEE Transactions on Information Theory." These articles cover the technologies at the heart of communications, signal processing, computer and control systems and serve as a valuable guide for all those interested in the basis for information theory.

Learning Theory

Author: Felipe Cucker
Publisher: Cambridge University Press
ISBN: 9781139462860
Release Date: 2007-03-29
Genre: Computers

The goal of learning theory is to approximate a function from sample values. To attain this goal learning theory draws on a variety of diverse subjects, specifically statistics, approximation theory, and algorithmics. Ideas from all these areas blended to form a subject whose many successful applications have triggered a rapid growth during the last two decades. This is the first book to give a general overview of the theoretical foundations of the subject emphasizing the approximation theory, while still giving a balanced overview. It is based on courses taught by the authors, and is reasonably self-contained so will appeal to a broad spectrum of researchers in learning theory and adjacent fields. It will also serve as an introduction for graduate students and others entering the field, who wish to see how the problems raised in learning theory relate to other disciplines.