Book contents
- Frontmatter
- Contents
- Introduction
- 1 Measure and integral
- 2 The Cauchy–Schwarz inequality
- 3 The AM–GM inequality
- 4 Convexity, and Jensen's inequality
- 5 The Lp spaces
- 6 Banach function spaces
- 7 Rearrangements
- 8 Maximal inequalities
- 9 Complex interpolation
- 10 Real interpolation
- 11 The Hilbert transform, and Hilbert's inequalities
- 12 Khintchine's inequality
- 13 Hypercontractive and logarithmic Sobolev inequalities
- 14 Hadamard's inequality
- 15 Hilbert space operator inequalities
- 16 Summing operators
- 17 Approximation numbers and eigenvalues
- 18 Grothendieck's inequality, type and cotype
- References
- Index of inequalities
- Index
1 - Measure and integral
Published online by Cambridge University Press: 06 July 2010
- Frontmatter
- Contents
- Introduction
- 1 Measure and integral
- 2 The Cauchy–Schwarz inequality
- 3 The AM–GM inequality
- 4 Convexity, and Jensen's inequality
- 5 The Lp spaces
- 6 Banach function spaces
- 7 Rearrangements
- 8 Maximal inequalities
- 9 Complex interpolation
- 10 Real interpolation
- 11 The Hilbert transform, and Hilbert's inequalities
- 12 Khintchine's inequality
- 13 Hypercontractive and logarithmic Sobolev inequalities
- 14 Hadamard's inequality
- 15 Hilbert space operator inequalities
- 16 Summing operators
- 17 Approximation numbers and eigenvalues
- 18 Grothendieck's inequality, type and cotype
- References
- Index of inequalities
- Index
Summary
Measure
Many of the inequalities that we shall establish originally concern finite sequences and finite sums. We then extend them to infinite sequences and infinite sums, and to functions and integrals, and it is these more general results that are useful in applications.
Although the applications can be useful in simple settings – concerning the Riemann integral of a continuous function, for example – the extensions are usually made by a limiting process. For this reason we need to work in the more general setting of measure theory, where appropriate limit theorems hold. We give a brief account of what we need to know; the details of the theory will not be needed, although it is hoped that the results that we eventually establish will encourage the reader to master them. If you are not familiar with measure theory, read through this chapter quickly, and then come back to it when you find that the need arises.
Suppose that Ω is a set. A measure ascribes a size to some of the subsets of Ω. It turns out that we usually cannot do this in a sensible way for all the subsets of Ω, and have to restrict attention to the measurable subsets of Ω. These are the ‘good’ subsets of Ω, and include all the sets that we meet in practice. The collection of measurable sets has a rich enough structure that we can carry out countable limiting operations.
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- Chapter
- Information
- Inequalities: A Journey into Linear Analysis , pp. 4 - 12Publisher: Cambridge University PressPrint publication year: 2007