Andere Kunden interessierten sich auch für
![Gaussian and Non-Gaussian Linear Time Series and Random Fields]( "Gaussian and Non-Gaussian Linear Time Series and Random Fields")
Gaussian and Non-Gaussian Linear Time Series and Random Fields77,99 €![Random and Quasi-Random Point Sets]( "Random and Quasi-Random Point Sets")
Random and Quasi-Random Point Sets77,99 €![Stochastic Visibility in Random Fields]( "Stochastic Visibility in Random Fields")
Stochastic Visibility in Random Fields88,99 €![Random Fields and Geometry]( "Random Fields and Geometry")
Random Fields and Geometry104,99 €![The Random-Cluster Model]( "The Random-Cluster Model")
The Random-Cluster Model92,99 €![The Art of Random Walks]( "The Art of Random Walks")
The Art of Random Walks39,99 €![Random Sums and Branching Stochastic Processes]( "Random Sums and Branching Stochastic Processes")
Random Sums and Branching Stochastic Processes77,99 €
This book aims to give a user friendly tutorial of an interdisciplinary research topic (fronts or interfaces in random media) to senior undergraduates and beginning grad uate students with basic knowledge of partial differential equations (PDE) and prob ability. The approach taken is semiformal, using elementary methods to introduce ideas and motivate results as much as possible, then outlining how to pursue rigor ous theorems, with details to be found in the references section. Since the topic concerns both differential equations and probability, and proba bility is traditionally a quite technical subject with a heavy measure theoretic com ponent, the book strives to develop a simplistic approach so that students can grasp the essentials of fronts and random media and their applications in a self contained tutorial. The book introduces three fundamental PDEs (the Burgers equation, Hamilton- Jacobi equations, and reaction-diffusion equations), analysis of their formulas and frontsolutions, and related stochastic processes. It builds up tools gradually, so that students are brought to the frontiers of research at a steady pace. A moderate number of exercises are provided to consolidate the concepts and ideas. The main methods are representation formulas of solutions, Laplace meth ods, homogenization, ergodic theory, central limit theorems, large deviation princi ples, variational principles, maximum principles, and Harnack inequalities, among others. These methods are normally covered in separate books on either differential equations or probability. It is my hope that this tutorial will help to illustrate how to combine these tools in solving concrete problems.