Probability, random processes, and statistical analysis
"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,...
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| Співавтор: | |
| Інші автори: | , |
| Формат: | Електронний ресурс eКнига |
| Мова: | Англійська |
| Опубліковано: |
Cambridge ; New York :
Cambridge University Press,
2012.
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| Предмети: | |
| Онлайн доступ: | An electronic book accessible through the World Wide Web; click to view |
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| Резюме: | "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's 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"-- |
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| Фізичний опис: | xxxi, 780 p. |
| Бібліографія: | Includes bibliographical references and index. |