Which Book is Best for Learning Fourier Analysis?

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Discussion Overview

The discussion centers around recommendations for books on Fourier analysis suitable for someone with a background in linear algebra, complex analysis, and basic real analysis. Participants share various titles and their suitability based on different levels of rigor and focus.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant suggests "Fourier Analysis and Its Applications" by Gerald B. Folland as a potential resource.
  • Another participant mentions "Applied Fourier Analysis" by Hwei Hsu, noting its use in their Communication Systems degree.
  • Discussion includes "Dym and McKean," which starts with an introduction to Lebesgue measure and integration, with some participants indicating it may be suitable if certain sections are skipped.
  • Stein's book is mentioned, with some participants noting its limitations regarding Riemann integrable functions and the treatment of Fourier transforms.
  • Some participants express a preference for Stein's book while acknowledging its restrictions on the types of functions covered.
  • Kammler's "A First Course in Fourier Analysis" is described as a more rigorous version of engineering-oriented treatments.
  • Howell's "Principles of Fourier Analysis" is noted for being mathematically oriented and comprehensive.
  • Katznelson's "Introduction to Harmonic Analysis" is recommended for those familiar with basic Lebesgue theory.
  • Körner's "Fourier Analysis" is mentioned as a collection of essays rather than a systematic textbook, appealing for its diverse applications.

Areas of Agreement / Disagreement

Participants present multiple competing views on the best resources for learning Fourier analysis, with no consensus on a single recommended text.

Contextual Notes

Some participants highlight limitations in the books mentioned, such as restrictions on the types of integrable functions and the scope of topics covered, which may affect their suitability depending on the reader's background.

desti
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Hi,

I am starting in a Ph.D. program in math next fall and the prerequisites for the first-year graduate course sequences included basics of Fourier analysis. The only thing I know about it is that you calculate a projection of a function on a certain infinite dimensional subspace, so I do know how to derive many of the really basic formulas.

I would like to find a good book that assumes you know linear algebra, complex analysis and basic real analysis (measure theoretic). What would you recommend?

Thanks in advance.
 
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You might want to look at "Fourier Analysis and Its Applications" by Gerald B. Folland. If this is not at a high enough level, then have a look at the Fourier analysis chapter in the Real Analysis grad text by the same author.
 
In my Communication Systems degree we used this book:-

Applied Fourier AnalysisAuthor: Hwei Hsu
Format: Paperback
Publication Date: October 1984
Publisher: Harcourt College Pub
Dimensions: 10.75"H x 8.25"W x 0.5"D; 1.05 lbs.
ISBN-10: 0156016095
ISBN-13: 9780156016094
 
Dym and McKean starts with a basic intro to the Lesbegue measure and integration so if you skip the few sections of the first chapter, the rest of the book is what you're looking for.

Stein would also be a good choice; however, his book on Fourier series only treats riemann integrable functions. But since the Fourier book is the first in a series, he develops the theory more and more in his complex and measure theory books.
 
Vid said:
Dym and McKean starts with a basic intro to the Lesbegue measure and integration so if you skip the few sections of the first chapter, the rest of the book is what you're looking for.

Stein would also be a good choice; however, his book on Fourier series only treats riemann integrable functions. But since the Fourier book is the first in a series, he develops the theory more and more in his complex and measure theory books.

I like Stein's book as well, but in addition to the restriction to Riemann integrable functions, which still allows a pretty good treatment of Fourier series, he also limits his treatment of Fourier transforms in Volume 1 to those of Schwartz (smooth and rapidly decaying) functions. Volume 3 covers the Lebesgue integral and then covers the Fourier transform on L^1 and L^2.

There was supposed to be a Volume 4 which would cover distribution theory (linear functionals on the space of Schwartz functions), which allows you to define Fourier transforms for a much broader range of function-like objects, but this volume appears never to have materialized.

[Note to the original poster to avoid confusion: we are referring above to the set of "Princeton Lectures in Analysis" undergraduate books by Stein and Shakarchi (volume 2 covers complex analysis, with a bit of Fourier content there as well), NOT the much more advanced graduate-level series by Stein and Weiss.]

There are other good books that cover the same material, though. I've only looked at excerpts of the following two, but from what I have seen, they look really nice and don't require the machinery of the Lebesgue intergral and measure theory (i.e., for the most part you can interpret the integrals as either Riemann or Lebesgue):

Kammler, "A First Course in Fourier Analysis" - this "feels" to me like a more rigorous version of the treatment you would see in an engineering-oriented book, particularly in terms of the applications covered. I seem to recall that Folland's Fourier analysis book is at about this level as well.

Howell, "Principles of Fourier Analysis" - more mathematically oriented, on about the same level as Stein and Shakarchi's Volume 1, but with a much more comprehensive treatment (and double the page count).

A really nice, efficient book that presumes you know the basic Lebesgue theory is Katznelson's "Introduction to Harmonic Analysis."

Finally, no discussion of Fourier analysis books should go without mentioning Körner's "Fourier Analysis," which is a bit unorthodox and not really a place to learn Fourier analysis in a systematic way, but rather a fascinating collection of mini-essays, mostly covering a wide variety of applications of Fourier analysis (both in the sense of "applied math" and in the sense of applications to other branches of pure math). This is well worth checking out.
 

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