Matrix-Analytic Methods in Stochastic Models
Guy Latouche · Vaidyanathan Ramaswami · Jay Sethuraman · Karl Sigman · Mark S. Squillante · David Yao
2012년 12월 · Springer Proceedings in Mathematics & Statistics 27권 · Springer Science & Business Media
eBook
258
페이지
report검증되지 않은 평점과 리뷰입니다. 자세히 알아보기
eBook 정보
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.
저자 정보
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
이 eBook 평가
의견을 알려주세요.
읽기 정보
스마트폰 및 태블릿
노트북 및 컴퓨터
컴퓨터의 웹브라우저를 사용하여 Google Play에서 구매한 오디오북을 들을 수 있습니다.
eReader 및 기타 기기
Kobo eReader 등의 eBook 리더기에서 읽으려면 파일을 다운로드하여 기기로 전송해야 합니다. 지원되는 eBook 리더기로 파일을 전송하려면 고객센터에서 자세한 안내를 따르세요.
