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Probability, random variables and stochastic processes 4th
The fourth edition of this book has been updated significantly from previous editions. arid it includes a coauthor. About one-third of the content of this edition is new material, and these additions are incorporated while maintaining the style and spirit of the previous editions that are familiar to many of its readers. The basic outlook and approach remain the same: To develop the subject of probability theory and stochastic processes as a deductive discipline and to illustrate the theory with basic applications of engineeling interest. To this extent. these remarks made in the first edition are still valid: "The book is written neither for the handbook-oriented students nor for the sophisticated few (if any) who can learn the subject from advanced mathematical texts. It is written for the majority of engineers and physicists who have sufficient maturity to appreciate and follow a logical presentation .... There is an obvious lack of continuity between the elements of probability as presented in introductory courses, and the sophisticated concepts needed in today's applications .... Random variables. transformations, expected values, conditional densities, characteristic functions cannot be mastered with mere exposure. These concepts must be clearly defined and must be developed, one at a time, with sufficient elaboration." Recognizing these factors, additional examples are added for further clarity, and the new topics include the following. Chapters 3 and 4 have ul)dergone substantial rewriting. Chapter 3 has a detailed section on Bernoulli's theorem and games of chance (Sec. 3-3), and several examples are presented there including the classical gambler's ruin problem to stimulate student interest. In Chap. 4 various probability distributions are categorized and illustrated, and two kinds of approximations to the binomial distribution are carried out to illustrate the connections among some of the random variables. " Chapter 5 contains new examples illustrating the usefulness of characteristic functions and moment-generating functions including the proof of the DeMoivre-Laplace theorem. Chapter 6 has been rewritten with additional examples, and is complete in its description of two random variables and their properties. Chapter 8 contains a new Sec. 8-3 on Parameter e6Eimation that includes key ideas on minimum variance unbiased estimation, the Cramer-Rao bound, the Rao-Blackwell theorem, and the Bhattacharya bound. PREFACE . In Chaps. 9 and la, sections on Poisson processes are further expanded with additional results. A new detailed section on random walks has also been added. Chapter 12 includes a new subsection describing the parametrization of the class of all admissible spectral extensions given a set of valid autocorrelations. Because of the importance of queueing theory, the old material has undergone complete revision to the extent that two new chapters (15 and 16) are devoted to this topic. Chapter 15 describes Markov chains, their properties, characterization, and the long-term (steady state) and transient behavior of the chain and illustrates various theorems through several examples. In particular, Example 15-26 The Game of Tennis is an excellent illustration of the theory to analyze practical applications, and the chapter concludes with a detailed study of branching processes, which have important applications in queueing theory. Chapter 16 describes Markov processes and queueing theory starting with the Chapman-Kolmogorov equations and concentrating on the birth-death processes to illustrate markovian queues. The treatment, however, includes non-markovian queues and machine servicing problems, and concludes with an introduction to the network of queues. The material in this book can be organized for various one semester courses: ? Chapters 1 to 6: Probability Theory (for senior andlor first-level graduate students) ? Chapters 7 and 8: Statistics and Estimation Theory (as a follow-up course to Probability Theory) ? Chapters 9 to 11: Stochastic Processes (follow-up course to Probability Theory.) ? Chapters 12 to 14: Spectrum Estimation and Filtering (follow-up course to Stochastic Processes) ? Chapters 15 and 16: Markov Chains and Queueing Theory (follow-up course to Probability Theory) The authors would like to thank Ms. Catherine Fields Shultz, editor for electrical and computer engineering at McGraw-Hill Publishing Company, Ms. Michelle Flomenhoft and Mr. John Griffin, developmental editors, Ms. Sheila Frank, Project manager and her highly efficient team, and Profs. D. P. Gelopulos, M. Georgiopoulos, A. Haddad, T. Moon, 1. Rowland, C. S. Tsang, J. K. Tugnait, and O. C. Ugweje, for their comments, criticism, and guidance throughout the period of this revision. In addition, Dr. Michael Rosse, several colleagues at Polytechnic including Profs. Dante Youla, Henry Bertoni, Leonard Shaw and Ivan Selesnick, as well as students Dr. Hyun Seok Oh. Mr. Jun Ho Jo. and Mr. Seung Hun Cha deserve special credit for their valuable help and encouragement during the preparation of the manuscript. Discussions with Prof. C. Radhakrishna Rao about two of his key theorems in statistics and other items are also gratefully acknowledged.
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| Tan 519. 2 Pap p | PSB lt.dasar - Pascasarjana | 2 |
| Penerbit | Singapore McGraw Hill., 2002 |
|---|---|
| Edisi | - |
| Subjek | Probabilities Random variables Stochstic processes |
| ISBN/ISSN | 0073660116 |
| Klasifikasi | NONE |
| Deskripsi Fisik | x, 852p; chart, tables, graphics, appendix, 14cm |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |