Probability, Random Processes, and Statistical Analysis (Hardcover) (ISBN-13: 9780521895446)

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 It process. Applications such as hidden Markov models (HMM), the Viterbi, BCJR, and Baum-Welch algorithms, algorithms for machine learning, Wiener and Kalman filters, queueing and loss networks, and 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. Professor Hisashi Kobayashi discusses the book:

Author: Hisashi Kobayashi, Brian L. Mark, William Turin
ISBN-10: 0521895448
ISBN-13: 9780521895446
Publisher: Cambridge University Press
Language: English
Published: 12/15/2011
Pages: 812
Format: Hardcover
Weight: 3.05lbs
Size: 9.70h x 6.90w x 1.90d