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The long-awaited revision of "Fundamentals of Applied
Probability and Random Processes" expands on the central components
that made the first edition a classic. The title is based on the
premise that engineers use probability as a modeling tool, and that
probability can be applied to the solution of engineering problems.
Engineers and students studying probability and random processes
also need to analyze data, and thus need some knowledge of
statistics. This book is designed to provide students with a
thorough grounding in probability and stochastic processes,
demonstrate their applicability to real-world problems, and
introduce the basics of statistics. The book's clear writing style
and homework problems make it ideal for the classroom or for
self-study.
Markov processes are processes that have limited memory. In particular, their dependence on the past is only through the previous state. They are used to model the behavior of many systems including communications systems, transportation networks, image segmentation and analysis, biological systems and DNA sequence analysis, random atomic motion and diffusion in physics, social mobility, population studies, epidemiology, animal and insect migration, queueing systems, resource management, dams, financial engineering, actuarial science, and decision systems. Covering a wide range of areas of application of Markov processes, this second edition is revised to highlight the most important aspects as well as the most recent trends and applications of Markov processes. The author spent over 16 years in the industry before returning to academia, and he has applied many of the principles covered in this book in multiple research projects. Therefore, this is an applications-oriented book that also includes enough theory to provide a solid ground in the subject for the reader.
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