Real Analysis: Measure Theory, Integration, and Hilbert Spaces
By addebook • Oct 3rd, 2008 • Category: Mathematics •
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Real Analysis: Measure Theory, Integration, and Hilbert Spaces (Princeton Lectures in Analysis, Volume 3)
Real Analysis: Measure Theory, Integration, and Hilbert Spaces (Princeton Lectures in Analysis)
By Elias M. Stein, Rami Shakarchi
Publisher: Princeton University Press
Number Of Pages: 392
Publication Date: 2005-03-14
ISBN-10 / ASIN: 0691113866
ISBN-13 / EAN: 9780691113869
Binding: Hardcover
Real Analysis is the third volume in the Princeton Lectures in Analysis, a series of four textbooks that aim to present, in an integrated manner, the core areas of analysis. Here the focus is on the development of measure and integration theory, differentiation and integration, Hilbert spaces, and Hausdorff measure and fractals. This book reflects the objective of the series as a whole: to make plain the organic unity that exists between the various parts of the subject, and to illustrate the wide applicability of ideas of analysis to other fields of mathematics and science.
After setting forth the basic facts of measure theory, Lebesgue integration, and differentiation on Euclidian spaces, the authors move to the elements of Hilbert space, via the L2 theory. They next present basic illustrations of these concepts from Fourier analysis, partial differential equations, and complex analysis. The final part of the book introduces the reader to the fascinating subject of fractional-dimensional sets, including Hausdorff measure, self-replicating sets, space-filling curves, and Besicovitch sets. Each chapter has a series of exercises, from the relatively easy to the more complex, that are tied directly to the text. A substantial number of hints encourage the reader to take on even the more challenging exercises.
As with the other volumes in the series, Real Analysis is accessible to students interested in such diverse disciplines as mathematics, physics, engineering, and finance, at both the undergraduate and graduate levels.
Also available, the first two volumes in the Princeton Lectures in Analysis:
Summary: great book
Rating: 5
i found the first three chapters of this book very clear and well written. i’d strongly recommend it for someone looking to learn about analysis on the real line.
Summary: Good book for reading and as a graduate student
Rating: 5
Easy to read. My university is using this book to get the graduate students ready for the real analysis qualifying exam. So go ahead and buy this book if you’re planning to work on a PhD in mathematics. If you’re not planning to work on a PhD in math, this is still a good book to read if you enjoy studying about the real line.
The book begins with measure theory, integration and differentiation. These are included in Chapters 1 to 3. Then in Chapters 4 and 5, we look into Hilbert spaces. This is similar to studying finite-dimensional inner-product spaces, but here, Hilbert space is infinite-dimensional. However, the analysis is very similar. If you know some linear algebra, it should feel like as if you have already read these two chapters.
Finally in Chapters 6 and 7, we see abstract measure theory, including Hausdorff measure, and we study fractals and self-similar sets. And this concludes the book.
Also recommend Walter Rudin’s Real Analysis.
Summary: Suffers from all the flaws of a 1st edition
Rating: 2
This book has a lot of problems. Several sections are poorly written/edited. Several important named theorems are not clearly labeled. Also some of the proofs contain typos or errors. The chapter on differentiation is particularly lacking. The chapter is poorly organized and presented. There is also a glaring TeX error in the chapter.
At Princeton this book is used as part of an undergraduate course, and it shows. This is not the ideal book for a graduate level course in real analysis(though I think it would be very well suited for advanced undergrads). Too much time is spent on Lebesgue measure and integration in the first 2 chapters, and abstract measure theory is not intoduced until chapter 6. Also the Monotone Class theorem is lacking from the chapter on abstract measure theory. Also, the book only touches on functional analysis in the two chapters on Hilbert spaces (where they assume all Hilbert spaces are separable).
On the other hand, the presentations of Lebesgue measure/integration and Hilbert spaces in the book are pretty good. The exercises and problems in teh book (when stated properly) are very good and instructive. Overall this book has a lot of potential to be very good, but seems to be suffering from a lack of revision. Hopefully these issues will be fixed in later editions.
Summary: Excellent sourse for graduate analysis
Rating: 5
This book is the best book on real analysis I have ever studied. It does a wonderful job in bridging undergraduate level with graduate level analysis. I have not seen any book that makes measure and Lebesgue theory so easy to understand.
The books begins by defining what a “measure” is all about. And the description is so intuitive and geometrical that you would wonder why you weren’t taught it this way before. The book then goes into Lebesgue theory and all of it suddenly becomes so easy.
The book has plenty of wonderful examples and a good set of over 30 problems per chapter.
Elias Stein (one of the authors) is a very renowned mathematician, and one need not worry about the accuracy of the proofs in the book–they are “bullet-proof”, and at the same time succinct.
If you are struggling with W. Rudin’s book on Analysis, this book is a MUST for you.
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