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Markovian Demand Inventory Models, Dirk Beyer; Feng Cheng; Suresh P. Sethi; Michael T


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Автор: Dirk Beyer; Feng Cheng; Suresh P. Sethi; Michael T
Название:  Markovian Demand Inventory Models
ISBN: 9781461424666
Издательство: Springer
Классификация:





ISBN-10: 1461424666
Обложка/Формат: Paperback
Страницы: 255
Вес: 0.39 кг.
Дата издания: 25.02.2012
Серия: International Series in Operations Research & Management Science
Язык: English
Размер: 234 x 156 x 15
Основная тема: Business and Management
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: With a particular focus on inventory models where these world events are modeled by Markov processes, the authors present their research on Markovian demand inventory models, which was carried out over a period of ten years beginning in the early nineties.


Stability Analysis of Markovian Jump Systems

Автор: Yu Kang; Yun-Bo Zhao; Ping Zhao
Название: Stability Analysis of Markovian Jump Systems
ISBN: 9811038597 ISBN-13(EAN): 9789811038594
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book focuses on the stability analysis of Markovian jump systems (MJSs) with various settings and discusses its applications in several different areas. It also presents general definitions of the necessary concepts and an overview of the recent developments in MJSs. Further, it addresses the general robust problem of Markovian jump linear systems (MJLSs), the asynchronous stability of a class of nonlinear systems, the robust adaptive control scheme for a class of nonlinear uncertain MJSs, the practical stability of MJSs and its applications as a modelling tool for networked control systems, Markovian-based control for wheeled mobile manipulators and the jump-linear-quadratic (JLQ) problem of a class of continuous-time MJLSs. It is a valuable resource for researchers and graduate students in the field of control theory and engineering.

Control and Filtering for Semi-Markovian Jump Systems

Автор: Fanbiao Li; Peng Shi; Ligang Wu
Название: Control and Filtering for Semi-Markovian Jump Systems
ISBN: 3319471988 ISBN-13(EAN): 9783319471983
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Integrated models in production planning, inventory, quality, and maintenance

Название: Integrated models in production planning, inventory, quality, and maintenance
ISBN: 1461356520 ISBN-13(EAN): 9781461356523
Издательство: Springer
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Цена: 22359.00 р.
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Описание: Prominent researchers, who are actively engaged in these areas, have contributed the topical chapters focused on the most recent issues in the area. In Part I, Ben-Daya and Rahim provide an overview of the literature dealing with integrated models for production, quality, and maintenance.

Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations

Автор: Micka?l D. Chekroun; Honghu Liu; Shouhong Wang
Название: Stochastic Parameterizing Manifolds and Non-Markovian Reduced Equations
ISBN: 3319125192 ISBN-13(EAN): 9783319125190
Издательство: Springer
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Цена: 6986.00 р.
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Описание: In this second volume, a general approach is developed to provide approximate parameterizations of the "small" scales by the "large" ones for a broad class of stochastic partial differential equations (SPDEs).


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