342 Pages
by
Chapman & Hall
330 Pages
by
Routledge
Also available as eBook on:
This book will enable researchers and students of analysis to more easily understand research papers in which probabilistic methods are used to prove theorems of analysis, many of which have no other known proofs. The book assumes a course in measure and integration theory but requires little or no background in probability theory. It emplhasizes topics of interest to analysts, including random series, martingales and Brownian motion.
Fourier transforms on Rd
Weak convergence in M1 (Rd)
Independende
Infinite series of random vectors
Normal distributions and central limits
Martingales
Projective limits and infinite products of probability measures
Brownian motions
Random Fourier series of continuous functions
Fourier coefficients of continuous functions
Weak convergence in M1 (Rd)
Independende
Infinite series of random vectors
Normal distributions and central limits
Martingales
Projective limits and infinite products of probability measures
Brownian motions
Random Fourier series of continuous functions
Fourier coefficients of continuous functions
Biography
Stromberg, Karl