Matrix-Analytic Methods in Stochastic Models
. Ed(s): Latouche, Guy; Ramaswami, Vaidyanathan; Sethuraman, Jay; Sigman, Karl; Squillante, Mark S.; Yao, David
ISBN 10: 1489994246 ISBN 13: 9781489994240
Published by Springer-Verlag New York Inc., 2015
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Editor(s): Latouche, Guy; Ramaswami, Vaidyanathan; Sethuraman, Jay; Sigman, Karl; Squillante, Mark S.; Yao, David. Series: Springer Proceedings in Mathematics and Statistics. Num Pages: 258 pages, biography. BIC Classification: KJT; PBKS; PBT. Category: (G) General (US: Trade). Dimension: 235 x 155 x 14. Weight in Grams: 421. . 2015. Paperback. . . . . Seller Inventory # V9781489994240
Synopsis:
Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research.
About the Author:
Guy Latouche, Université Libre de Bruxelles, Belgium
Vaidyanathan Ramaswami , AT&T Labs Research, USA
Jay Sethuraman, Columbia University, USA
Karl Sigman, Columbia University, USA
Mark S. Squillante, IBM Thomas J. Watson Research Center, USA
David D. Yao, Columbia University, USA
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Bibliographic Details
Title: Matrix-Analytic Methods in Stochastic Models
Publisher: Springer-Verlag New York Inc.
Publication Date: 2015
Binding: Soft cover
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Matrix-Analytic Methods in Stochastic Models
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research. 272 pp. Englisch. Seller Inventory # 9781489994240
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Matrix-Analytic Methods in Stochastic Models
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch. Seller Inventory # 9781489994240
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Matrix-analytic and related methods have become recognized as an important and fundamental approach for the mathematical analysis of general classes of complex stochastic models. Research in the area of matrix-analytic and related methods seeks to discover underlying probabilistic structures intrinsic in such stochastic models, develop numerical algorithms for computing functionals (e.g., performance measures) of the underlying stochastic processes, and apply these probabilistic structures and/or computational algorithms within a wide variety of fields. This volume presents recent research results on: the theory, algorithms and methodologies concerning matrix-analytic and related methods in stochastic models; and the application of matrix-analytic and related methods in various fields, which includes but is not limited to computer science and engineering, communication networks and telephony, electrical and industrial engineering, operations research, management science, financial and risk analysis, and bio-statistics. These research studies provide deep insights and understanding of the stochastic models of interest from a mathematics and/or applications perspective, as well as identify directions for future research. Seller Inventory # 9781489994240
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