Probability, Random Processes, and Statistical Analysis : Applications to Communications, Signal Processing, Queueing Theory and Mathematical Finance

Together with the fundamental topics, this book covers advanced theories and engineering applications, including the EM algorithm, hidden Markov models, and queueing and loss systems. A solutions manual, lecture slides and MATLAB programs all available online make this ideal for classroom teaching as well as a valuable reference for professionals.

Together with the fundamentals of probability, random processes and statistical analysis, this insightful book also presents a broad range of advanced topics and applications. There is extensive coverage of Bayesian vs. frequentist statistics, time series and spectral representation, inequalities, bound and approximation, maximum-likelihood estimation and the expectation-maximization (EM) algorithm, geometric Brownian motion and Itô process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum–Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, and queueing and loss networks are treated in detail. The book will be useful to students and researchers in such areas as communications, signal processing, networks, machine learning, bioinformatics, econometrics and mathematical finance. With a solutions manual, lecture slides, supplementary materials and MATLAB programs all available online, it is ideal for classroom teaching as well as a valuable reference for professionals.