Latouche, G., Ramaswami, V., Sethuraman, J., Sigman, K., Squillante, M.S., Yao, D. (Eds.)
2013, XIV, 256 p. 47 illus.
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The only forum on the theoretical, algorithmic and methodological aspects of matrix-analytic and related methods in stochastic models, and their application across various fields
This area of mathematics and its applications have grown and advanced tremendously over the past few years from the previous original and early developments in the area
Presents the latest advances in this very important area of mathematics, as well as the latest advances in the applications of this area of mathematics across a broad spectrum of fields
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 applications perspective, as well as identify directions for future research.