Probability and Stochastic Processes with Applications
This text assumes no prerequisites in probability, a basic exposure to
calculus and linear algebra is necessary. Some real analysis as well as some
background in topology and functional analysis can be helpful. This note covers
the following topics: Limit theorems, Probability spaces, random variables,
independence, Markov operators, Discrete Stochastic Processes, Continuous
Stochastic Processes, Random Jacobi matrices, Symmetric Diophantine Equations
and Vlasov dynamics.
Author(s): Oliver
Knill
382 Pages