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.
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, 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:
Kobayashi and Mark present the most up-to-date analytical models, simulation techniques, and computational algorithms useful for performance evaluation of complex systems - including computer systems, communication networks, transportation systems, and manufacturing systems. Broader in scope than other texts, this book provides more in-depth coverage of topics such as computational algorithms and approximations. It appeals to students with a background or interest in a wide range of areas, including systems analysis or telecommunication networks."--Publisher's website.
Tokyo Seven Roses' is set in Japan during the waning months of WWII and the beginning of the Occupation. It is written as a diary kept from April 1945 to April 1946 by Shinsuke Yamanaka, a fifty-three-year-old fan-maker living in Nezu, part of Tokyo's shitamachi (old-town) district. After the war, Shinsuke learns by chance that the Occupation forces are plotting a nefarious scheme: in order to cut Japan off from its dreadful past, they intend to see that the language is written henceforth using the alphabet. To fight off this unheard-of threat to the integrity of Japanese culture, seven beautiful women – the Seven Roses – take a stand.
Tokyo Seven Roses' is set in Japan during the waning months of WWII and the beginning of the Occupation. It is written as a diary kept from April 1945 to April 1946 by Shinsuke Yamanaka, a fifty-three-year-old fan-maker living in Nezu, part of Tokyo's shitamachi (old-town) district. After the war, Shinsuke learns by chance that the Occupation forces are plotting a nefarious scheme: in order to cut Japan off from its dreadful past, they intend to see that the language is written henceforth using the alphabet. To fight off this unheard-of threat to the integrity of Japanese culture, seven beautiful women – the Seven Roses – take a stand.
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.
This book is a self-contained introduction to the theory of periodic, progressive, permanent waves on the surface of incompressible inviscid fluid. The problem of permanent water-waves has attracted a large number of physicists and mathematicians since Stokes' pioneering papers appeared in 1847 and 1880. Among many aspects of the problem, the authors focus on periodic progressive waves, which mean waves traveling at a constant speed with no change of shape. As a consequence, everything about standing waves are excluded and solitary waves are studied only partly. However, even for this restricted problem, quite a number of papers and books, in physics and mathematics, have appeared and more will continue to appear, showing the richness of the subject. In fact, there remain many open questions to be answered.The present book consists of two parts: numerical experiments and normal form analysis of the bifurcation equations. Prerequisite for reading it is an elementary knowledge of the Euler equations for incompressible inviscid fluid and of bifurcation theory. Readers are also expected to know functional analysis at an elementary level. Numerical experiments are reported so that any reader can re-examine the results with minimal labor: the methods used in this book are well-known and are described as clearly as possible. Thus, the reader with an elementary knowledge of numerical computation will have little difficulty in the re-examination.
Kobayashi and Mark present the most up-to-date analytical models, simulation techniques, and computational algorithms useful for performance evaluation of complex systems - including computer systems, communication networks, transportation systems, and manufacturing systems. Broader in scope than other texts, this book provides more in-depth coverage of topics such as computational algorithms and approximations. It appeals to students with a background or interest in a wide range of areas, including systems analysis or telecommunication networks."--Publisher's website.
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.