概率论与随机过程中的泛函分析（影印版）

本书主要包含国外反映近代数学发展的纯数学与应用数学方面的优秀书籍，天元基金邀请国内各个方向的知名数学家参与选题的工作，经专家遴选、推荐而出版。 目录 Preface 1 Preliminaries, notations and conventions 1.1 Elements of topology 1.2 Measure theory 1.3 Functions of bounded variation. Riemann-Stieltjes integral 1.4 Sequences of independent random variables 1.5 Convex functions. Holder and Minkowski inequalities 1.6 The Cauchy equation 2 Basic notions in functional analysis 2.1 Linear spaces 2.2 Banach spaces 2.3 The space of bounded linear operators 3 Conditional expectation 3.1 Projections in Hilbert spaces 3.2 Definition and existence of conditional expectation 3.3 Properties and examples 3.4 The Radon-Nikodym Theorem 3.5 Examples of discrete martingales 3.6 Convergence of self-adjoint operators 3.7 ... and of martingales 4 Brownian motion and l-Iilbert spaces 4.1 Gaussian families & the definition of Brownian motion 4.2 Complete orthonormal sequences in a Hilbert space 4.3 Construction and basic properties of Brownian motion 4.4 Stochastic integrals 5 Dual spaces and convergence of probability measures 5.1 The Hahn-Banach Theorem 5.2 Form of linear functionals in specific Banach spaces 5.3 Thedual of an operator 5.4 Weak and weak* topologies 5.5 The Central Limit Theorem 5.6 Weak convergence in metric spaces 5.7 Compactness everywhere 5.8 Notes on other modes of convergence 6 The Gelfand transform and its applications 6.1 Banach algebras 6.2 The Gelfand transform 6.3 Examples of Gelfand transform 6.4 Examples of explicit calculations of Gelfand transform 6.5 Dense subalgebras of C(S) 6.6 Inverting the abstract Fourier transform 6.7 The Factorization Theorem 7 Semigroups of operators and Levy processes 7.1 The Banach-Steinhaus Theorem 7.2 Calculus of Banach space valued functions 7.3 Closed operators 7.4 Semigroups of operators 7.5 Brownian motion and Poisson process semigroups 7.6 More convolution semigroups 7.7 The telegraph process semigroup 7.8 Convolution semigroups of measures on semigroups 8 Markov processes and semigroups of operators 8.1 Semigroups of operators related to Markov processes 8.2 The Hille-Yosida Theorem 8.3 Generators of stochastic processes 8.4 Approximation theorems 9 Appendixes 9.1 Bibliographical notes 9.2 Solutions and hints to exercises 9.3 Some commonly used notations References Index