Random Processes for Engineers ─ A Primer

This book discusses the statistical description of processes, including an extensive review of probability and statistics, and the analysis of raw data using spectral methods. Various theoretical models that have been proposed for processes (ARMA, Bernoulli, shot, Markov, and random walks) are described, as well as techniques that are used for prediction of such processes: least meansquared error in general, Wiener-Hopf and Kalman filters. Everything in this book is introduced at a nuts and bolts level and fills in the gap between the undergraduate engineering statistics course and the rigorous approaches students will encounter upon further study.

Dr. Arthur David Snider has 50+ years of experience in modeling physical systems in the areas of heat transfer, electromagnetics, microwave circuits, and orbital mechanics, as well as the mathematical areas of numerical analysis, signal processing, differential equations, and optimization.

Dr. Snider has degrees in mathematics (BS, MIT; PhD, NYU) and physics (MA, Boston U), and he is a registered professional engineer. He served for 45 years on the faculties of mathematics, physics, and electrical engineering at the University of South Florida. He worked 5 years as a systems analyst at MIT's Draper Instrumentation Lab and has consulted in many industries in Florida.