The core chapters of this volume provide a complete course on metric, normed, and Hilbert spaces, and include many results and exercises seldom found in texts on analysis at this level. The author covers an unusually wide range of material in a clear and concise format including elementary real anal
Foundations of Real and Abstract Analysis
β Scribed by Douglas S. Bridges (auth.)
- Publisher
- Springer-Verlag New York
- Year
- 1998
- Tongue
- English
- Leaves
- 328
- Series
- Graduate Texts in Mathematics 174
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, length; and in Chapter 5, inner product. In addition to the standard topics that, arguably, should form part of the armoury of any graduate student in mathematics, physics, mathematical economics, theoretical statistics,. . . , this part of the book contains many results and exercises that are seldom found in texts on analysis at this level. Examples of the latter are Wongβs Theorem(3. 3. 12)showingthattheLebesguecoveringpropertyisequivalent to the uniform continuity property, and Motzkinβs result (5. 2. 2) that a nonempty closed subset of Euclidean space has the unique closest point property if and only if it is convex. The sad reality today is that, perceiving them as one of the harder parts oftheirmathematicalstudies,studentscontrivetoavoidanalysiscoursesat almost any cost, in particular that of their own educational and technical deprivation. Many universities have at times capitulated to the negative demand of students for analysis courses and have seriously watered down their expectations of students in that area. As a result, mathematics - jors are graduating, sometimes with high honours, with little exposure to anything but a rudimentary course or two on real and complex analysis, often without even an introduction to the Lebesgue integral.
β¦ Table of Contents
Introduction....Pages 1-8
Front Matter....Pages 9-9
Analysis on the Real Line....Pages 11-77
Differentiation and the Lebesgue Integral....Pages 79-122
Front Matter....Pages 123-123
Analysis in Metric Spaces....Pages 125-171
Analysis in Normed Linear Spaces....Pages 173-231
Hilbert Spaces....Pages 233-258
An Introduction to Functional Analysis....Pages 259-290
β¦ Subjects
Real Functions; Operations Research/Decision Theory
π SIMILAR VOLUMES
While at times the logic of this book is very clear, I would not say this is a good book. I would not recommend it for self study, and I think it would be a terrible choice of a textbook at any level. It might be useful for someone who already knows the material and wants a concise review of it, b
<p>The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, le
A complete course on metric, normed, and Hilbert spaces, including many results and exercises seldom found in texts on analysis at this level. The author covers an unusually wide range of material in a clear and concise format, including elementary real analysis, Lebesgue integration on R, and an in
<p>The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, le