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Sinopsis
The random phenomena can be described by stochastic processes. This book provides a systematic treatment of stochastic processes and their applications emphasizing the examples in engineering and management fields with numerous illustrations.
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Reseña del editor
This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering systems, physics, biology, operations research, business, economics, psychology, and linguistics. Stochastic modeling is one of the promising kinds of modeling in applied probability theory. This book is intended to introduce basic stochastic processes: Poisson pro cesses, renewal processes, discrete-time Markov chains, continuous-time Markov chains, and Markov-renewal processes. These basic processes are introduced from the viewpoint of elementary mathematics without going into rigorous treatments. This book also introduces applied stochastic system modeling such as reliability and queueing modeling. Chapters 1 and 2 deal with probability theory, which is basic and prerequisite to the following chapters. Many important concepts of probabilities, random variables, and probability distributions are introduced. Chapter 3 develops the Poisson process, which is one of the basic and im portant stochastic processes. Chapter 4 presents the renewal process. Renewal theoretic arguments are then used to analyze applied stochastic models. Chapter 5 develops discrete-time Markov chains. Following Chapter 5, Chapter 6 deals with continuous-time Markov chains. Continuous-time Markov chains have im portant applications to queueing models as seen in Chapter 9. A one-semester course or two-quarter course consists of a brief review of Chapters 1 and 2, fol lowed in order by Chapters 3 through 6.
Reseña del editor
This book provides a self-contained and systematic treatment of stochastic processes and their applications. Having a ba- sic knowledge of mathematics at an undergraduate level, the reader can easily understand stochastic processes with dis- crete state space such as Poisson processes, renewal proces- ses and Markov chains. Fruitful applications of such proces- sesare also described in the real world problems in relia- bility and queueing models. Numerous illustrations are included for better understanding. Problems are included in each chapter. Appendices are devoted to the Laplace-Stieltjes transforms and their properties, and answers to selected problems. It is suitable for an introductory one-semester or two-quarter course in stochastic processes for the junior or senior undergraduate students.
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Applied Stochastic System Modeling
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Springer Berlin Heidelberg, 2011
ISBN 10: 3642846831
ISBN 13: 9783642846830
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Applied Stochastic System Modeling
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Applied Stochastic System Modeling
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Springer Berlin Heidelberg Dez 2011, 2011
ISBN 10: 3642846831
ISBN 13: 9783642846830
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering systems, physics, biology, operations research, business, economics, psychology, and linguistics. Stochastic modeling is one of the promising kinds of modeling in applied probability theory. This book is intended to introduce basic stochastic processes: Poisson pro cesses, renewal processes, discrete-time Markov chains, continuous-time Markov chains, and Markov-renewal processes. These basic processes are introduced from the viewpoint of elementary mathematics without going into rigorous treatments. This book also introduces applied stochastic system modeling such as reliability and queueing modeling. Chapters 1 and 2 deal with probability theory, which is basic and prerequisite to the following chapters. Many important concepts of probabilities, random variables, and probability distributions are introduced. Chapter 3 develops the Poisson process, which is one of the basic and im portant stochastic processes. Chapter 4 presents the renewal process. Renewal theoretic arguments are then used to analyze applied stochastic models. Chapter 5 develops discrete-time Markov chains. Following Chapter 5, Chapter 6 deals with continuous-time Markov chains. Continuous-time Markov chains have im portant applications to queueing models as seen in Chapter 9. A one-semester course or two-quarter course consists of a brief review of Chapters 1 and 2, fol lowed in order by Chapters 3 through 6. 284 pp. Englisch. Nº de ref. del artículo: 9783642846830
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Applied Stochastic System Modeling
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Springer Berlin Heidelberg, 2011
ISBN 10: 3642846831
ISBN 13: 9783642846830
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are applied in many fields such as engineering systems, physics, biology, operations research, business, economics, psychology, and linguistics. Stochastic modeling is one of the promising kinds of modeling in applied probability theory. This book is intended to introduce basic stochastic processes: Poisson pro cesses, renewal processes, discrete-time Markov chains, continuous-time Markov chains, and Markov-renewal processes. These basic processes are introduced from the viewpoint of elementary mathematics without going into rigorous treatments. This book also introduces applied stochastic system modeling such as reliability and queueing modeling. Chapters 1 and 2 deal with probability theory, which is basic and prerequisite to the following chapters. Many important concepts of probabilities, random variables, and probability distributions are introduced. Chapter 3 develops the Poisson process, which is one of the basic and im portant stochastic processes. Chapter 4 presents the renewal process. Renewal theoretic arguments are then used to analyze applied stochastic models. Chapter 5 develops discrete-time Markov chains. Following Chapter 5, Chapter 6 deals with continuous-time Markov chains. Continuous-time Markov chains have im portant applications to queueing models as seen in Chapter 9. A one-semester course or two-quarter course consists of a brief review of Chapters 1 and 2, fol lowed in order by Chapters 3 through 6. Nº de ref. del artículo: 9783642846830
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Applied Stochastic System Modeling
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Springer Berlin Heidelberg, 2011
ISBN 10: 3642846831
ISBN 13: 9783642846830
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book was written for an introductory one-semester or two-quarter course in stochastic processes and their applications. The reader is assumed to have a basic knowledge of analysis and linear algebra at an undergraduate level. Stochastic models are appl. Nº de ref. del artículo: 5072147
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Applied Stochastic System Modeling
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Applied Stochastic System Modeling
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Applied Stochastic System Modeling
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ISBN 10: 3642846831
ISBN 13: 9783642846830
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Condición: New. Num Pages: 269 pages, 10 black & white tables, biography. BIC Classification: KCA; KJT. Category: (P) Professional & Vocational. Dimension: 244 x 170 x 15. Weight in Grams: 494. . 2011. Softcover reprint of the original 1st ed. 1992. Paperback. . . . . Nº de ref. del artículo: V9783642846830
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