Fourier Analysis in Probability Theory

Fourier Analysis in Probability Theory

1st Edition - January 28, 1972

Write a review

  • Author: Tatsuo Kawata
  • eBook ISBN: 9781483218526

Purchase options

Purchase options
DRM-free (PDF)
Sales tax will be calculated at check-out

Institutional Subscription

Free Global Shipping
No minimum order

Description

Fourier Analysis in Probability Theory provides useful results from the theories of Fourier series, Fourier transforms, Laplace transforms, and other related studies. This 14-chapter work highlights the clarification of the interactions and analogies among these theories. Chapters 1 to 8 present the elements of classical Fourier analysis, in the context of their applications to probability theory. Chapters 9 to 14 are devoted to basic results from the theory of characteristic functions of probability distributors, the convergence of distribution functions in terms of characteristic functions, and series of independent random variables. This book will be of value to mathematicians, engineers, teachers, and students.

Table of Contents


  • Preface

    I Introduction

    1.1 Measurable Space; Probability Space

    1.2 Measurable Functions; Random Variables

    1.3 Product Space

    1.4 Integrals

    1.5 The Fubini-Tonelli Theorem

    1.6 Integrals on R1

    1.7 Functions of Bounded Variation

    1.8 Signed Measure; Decomposition Theorems

    1.9 The Lebesgue Integral on R1

    1.10 Inequalities

    1.11 Convex Functions

    1.12 Analytic Functions

    1.13 Jensen's and Carleman's Theorems

    1.14 Analytic Continuation

    1.15 Maximum Modulus Theorem and Theorems of Phragmén-Lindelöf

    1.16 Inner Product Space

    II Fourier Series and Fourier Transforms

    2.1 The Riemann-Lebesgue Lemma

    2.2 Fourier Series

    2.3 The Fourier Transform of a Function in L1(—∞, ∞)

    2.4 Magnitude of Fourier Coefficients; the Continuity Modulus

    2.5 More About the Magnitude of Fourier Coefficients

    2.6 Some Elementary Lemmas

    2.7 Continuity and Magnitude of Fourier Transforms

    2.8 Operations on Fourier Series

    2.9 Operations on Fourier Transforms

    2.10 Completeness of Trigonometric Functions

    2.11 Unicity Theorem for Fourier Transforms

    2.12 Fourier Series and Fourier Transform of Convolutions

    Notes

    III Fourier-Stieltjes Coefficients, Fourier-Stieltjes Transforms and Characteristic Functions

    3.1 Monotone Functions and Distribution Functions

    3.2 Fourier-Stieltjes Series

    3.3 Average of Fourier-Stieltjes Coefficients

    3.4 Unicity Theorem for Fourier-Stieltjes Coefficients

    3.5 Fourier-Stieltjes Transform and Characteristic Function

    3.6 Periodic Characteristic Functions

    3.7 Some Inequality Relations for Characteristic Functions

    3.8 Average of a Characteristic Function

    3.9 Convolution of Nondecreasing Functions

    3.10 The Fourier-Stieltjes Transform of a Convolution and the Bernoulli Convolution

    Notes

    IV Convergence and Summability Theorems

    4.1 Convergence of Fourier Series

    4.2 Convergence of Fourier-Stieltjes Series

    4.3 Fourier's Integral Theorems; Inversion Formulas for Fourier Transforms

    4.4 Inversion Formula for Fourier-Stieltjes Transforms

    4.5 Summability

    4.6 (C,1)-Summability for Fourier Series

    4.7 Abel-Summability for Fourier Series

    4.8 Summability Theorems for Fourier Transforms

    4.9 Determination of the Absolutely Continuous Component of a Nondecreasing Function

    4.10 Fourier Series and Approximate Fourier Series of a Fourier-Stieltjes Transform

    4.11 Some Examples, Using Fourier Transforms

    Notes

    V General Convergence Theorems

    5.1 Nature of the Problems

    5.2 Some General Convergence Theorems I

    5.3 Some General Convergence Theorems II

    5.4 General Convergence Theorems for the Stieltjes Integral

    5.5 Wiener's Formula

    5.6 Applications of General Convergence Theorems to the Estimates of a Distribution Function

    Notes

    VI L2-Theory of Fourier Series and Fourier Transforms

    6.1 Fourier Series in an Inner Product Space

    6.2 Fourier Transform of a Function in L2(-∞, ∞)

    6.3 The Class H2 of Analytic Functions

    6.4 A Theorem of Szegö and Smirnov

    6.5 The Class ƃ2 of Analytic Functions

    6.6 A Theorem of Paley and Wiener

    Notes

    VII Laplace and Mellin Transforms

    7.1 The Laplace Transform

    7.2 The Convergence Abscissa

    7.3 Analyticity of a Laplace-Stieltjes Transform

    7.4 Inversion Formulas for Laplace Transforms

    7.5 The Laplace Transform of a Convolution

    7.6 Operations of Laplace Transforms and Some Examples

    7.7 The Bilateral Laplace-Stieltjes Transform

    7.8 Mellin-Stieltjes Transforms

    7.9 The Mellin Transform

    Notes

    VIII More Theorems on Fourier and Laplace Transforms

    8.1 A Theorem of Hardy

    8.2 A Theorem of Paley and Wiener on Exponential Entire Functions

    8.3 Theorems of Ingham and Levinson

    8.4 Singularities of Laplace Transforms

    8.5 Abelian Theorems for Laplace Transforms

    8.6 Tauberian Theorems

    8.7 Multiple Fourier Series and Transforms

    8.8 Nondecreasing Functions and Distribution Functions in Rm

    8.9 The Multiple Fourier-Stieltjes Transform

    Notes

    IX Convergence of Distribution Functions and Characteristic Functions

    9.1 Helly Theorems and Convergence of Nondecreasing Functions

    9.2 Convergence of Distribution Functions with Bounded Spectra

    9.3 Convergence of Distribution Functions

    9.4 Continuous Distribution Functions: A General Integral Transform of a Characteristic Function

    9.5 A Basic Theorem on Analytic Characteristic Functions

    9.6 Continuity Theorems on Intervals and Uniqueness Theorems

    9.7 The Compact Set of Characteristic Functions

    Notes

    X Some Properties of Characteristic Functions

    10.1 Characteristic Properties of Fourier Coefficients

    10.2 Basic Theorems on Characterization of a Characteristic Function

    103. Characteristic Properties of Characteristic Functions

    10.4 Functions of the Wiener Class

    10.5 Some Sufficient Criteria for Characteristic Functions

    10.6 More Criteria for Characteristic Functions

    Notes

    XI Distribution Functions and their Characteristic Functions

    11.1 Moments, Basic Properties

    11.2 Smoothness of a Characteristic Function and the Existence of Moments

    11.3 More About Smoothness of Characteristic Functions and Existence of Moments

    11.4 Absolute Moments

    11.5 Boundedness of the Spectra of Distribution Functions

    11.6 Integrable Characteristic Functions

    11.7 Analyticity of Distribution Functions

    11.8 Mean Concentration Function of a Distribution Function

    11.9 Some Properties of Analytic Characteristic Functions

    11.10 Characteristic Functions Analytic in the Half-Plane

    11.11 Entire Characteristic Functions I

    11.12 Entire Characteristic Functions II

    Notes

    XII Convergence of Series of Independent Random Variables

    12.1 Convergence of a Sequence of Random Variables

    12.2 The Borel Theorem

    12.3 The Zero-One Law

    12.4 The Equivalence Theorem

    12.5 The Three Series Theorem

    12.6 Sufficient Conditions for the Convergence of a Series

    12.7 Convergence Criteria and the Typical Function

    12.8 Rademacher and Steinhaus Functions

    12.9 Convergence of Products of Characteristic Functions

    12.10 Unconditional Convergence

    12.11 Absolute Convergence

    12.12 Essential Convergence

    Notes

    XIII Properties of Sums of Independent Random Variables; Convergence of Series in the Mean

    13.1 Continuity and Discontinuity Properties of the Sum of a Series

    13.2 Integrability of the Sum of a Series

    13.3 Magnitude of the Characteristic Functions of the Sums of Series

    13.4 Distribution Functions of the Sums of Rademacher Series; Characteristic Functions of Singular Distributions

    13.5 Further Theorems on Rademacher Series

    13.6 Sums of Independent Random Variables

    13.7 Convergent Systems

    13.8 Integrability of Sums of Series; Strong and Weak Convergences of Series

    13.9 Vanishing of the Sum of a Series

    13.10 Summability of Series

    Notes

    XIV Some Special Series of Random Variables

    14.1 Fourier Series with Rademacher Coefficients

    14.2 Random Fourier Series

    14.3 Random Power Series, Convergence

    14.4 Convergence of Random Power Series with Identically and Independently Distributed Random Coefficients

    14.5 Analytic Continuation of Random Power Series

    14.6 Fourier Series with Orthogonal Random Coefficients

    Notes

    References

    Index

Product details

  • No. of pages: 680
  • Language: English
  • Copyright: © Academic Press 1972
  • Published: January 28, 1972
  • Imprint: Academic Press
  • eBook ISBN: 9781483218526

About the Author

Tatsuo Kawata

About the Editors

Z. W. Birnbaum

E. Lukacs

Affiliations and Expertise

Bowling Green State University

Ratings and Reviews

Write a review

There are currently no reviews for "Fourier Analysis in Probability Theory"