This book gives a concise introduction to the classical theory of
stochastic partial differential equations (SPDEs). It begins by
describing the classes of equations which are studied later in the book,
together with a list of motivating examples of SPDEs which are used in
physics, population dynamics, neurophysiology, finance and signal
processing. The central part of the book studies SPDEs as
infinite-dimensional SDEs, based on the variational approach to PDEs.
This extends both the classical Itô formulation and the martingale
problem approach due to Stroock and Varadhan. The final chapter
considers the solution of a space-time white noise-driven SPDE as a
real-valued function of time and (one-dimensional) space. The results of
J. Walsh's St Flour notes on the existence, uniqueness and Hölder
regularity of the solution are presented. In addition, conditions are
given under which the solution remains nonnegative, and the Malliavin
calculus is applied. Lastly, reflected SPDEs and their connection with
super Brownian motion are considered.
At a time when new sophisticated branches of the subject are being
developed, this book will be a welcome reference on classical SPDEs for
newcomers to the theory.