Probability and Information - Adobe eBook Reader - Publication
date:August 2008 - 65 b/w illus. 3 tables 240 exercises This new
and updated textbook is an excellent way to introduce
probability and information theory to students new to
mathematics, computer science, engineering, statistics,
economics, or business studies. Only requiring knowledge of
basic calculus, it begins by building a clear and systematic
foundation to probability and information. Classic topics
covered include discrete and continuous random variables,
entropy and mutual information, maximum entropy methods, the
central limit theorem and the coding and transmission of
information. Newly covered for this edition is modern material
on Markov chains and their entropy. Examples and exercises are
included to illustrate how to use the theory in a wide range of
applications, with detailed solutions to most exercises
available online for instructors.