An in-depth look at real analysis and its applications-now expanded and revised. This new edition of the widely used analysis book continues to cover real analysis in greater detail and at a more advanced level than most books on the subject. Encompassing several subjects that underlie much of modern analysis, the book focuses on measure and integration theory, point set topology, and the basics of functional analysis. It illustrates the use of the general theories and introduces readers to other branches of analysis such as Fourier analysis, distribution theory, and probability theory. This edition is bolstered in content as well as in scope-extending its usefulness to students outside of pure analysis as well as those interested in dynamical systems. The numerous exercises, extensive bibliography, and review chapter on sets and metric spaces make Real Analysis: Modern Techniques and Their Applications, Second Edition invaluable for students in graduate-level analysis courses. New features include: * Revised material on the n-dimensional Lebesgue integral. * An improved proof of Tychonoff's theorem. * Expanded material on Fourier analysis. * A newly written chapter devoted to distributions and differential equations. * Updated material on Hausdorff dimension and fractal dimension.

ε空间 I:实分析(第三年的数学博客选文)(英文版)》内容包括：测度论中的高级专题，尤其是Lebesgue—Radon—Nikodym定理和Riesz表示定理；泛函分析专题，如Hilbert空间和Banach空间；广义函数空间和重要的函数空间，包括Lebesgue的Lp空间和Sobolev空间。另外还讨论了Fourier变换的一般理论。《ε空间 I:实分析(第三年的数学博客选文)(英文版)》的第二部分谈到了许多辅助论题，诸如Zorn引理、Carathéodory延拓定理和Banach—Tarski悖论。作者还讨论了ε正规化推理——软分析的一个基本技巧，《ε空间 I:实分析(第三年的数学博客选文)(英文版)》书名正取于此意。总体来说，《ε空间 I:实分析(第三年的数学博客选文)(英文版)》提供了比二年级研究生实分析课程丰富得多的内容。

This concise guide to real analysis covers the core material of a graduate level real analysis course. On the abstract level, it covers the theory of measure and integration and the basics of point set topology, functional analysis, and the most important types of function spaces. On the more concrete level, it also deals with the applications of these general theories to analysis on Euclidean space: the Lebesgue integral, Hausdorff measure, convolutions, Fourier series and transforms, and distributions. The relevant definitions and major theorems are stated in detail. Proofs, however, are generally presented only as sketches, in such a way that the key ideas are explained but the technical details are omitted. In this way a large amount of material is presented in a concise and readable form. The prerequisite is a familiarity with classical real-variable theory.