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Stochastic Modelling Control by Davis Mark (19 results)
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£ 14.06
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Add to basketHardcover. Condition: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 1.23.
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Stochastic Modelling and Control (Monographs on Statistics and Applied Probability)
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Stochastic Modelling and Control
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Add to basketPaperback or Softback. Condition: New. Stochastic Modelling and Control 1.04. Book.
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Stochastic Modelling and Control
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Stochastic Modelling and Control
Published by Springer Netherlands, 2012
ISBN 10: 9401086400 ISBN 13: 9789401086400
Language: English
£ 52.91
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Add to basketTaschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.
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Stochastic Modelling and Control
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Stochastic Modelling and Control
Published by Springer Netherlands, 2012
ISBN 10: 9401086400 ISBN 13: 9789401086400
Language: English
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Add to basketHardcover. Condition: Good. 0412162008 Good; Hardcover; 1985, Springer-Verlag Publishing; Former library copy with standard library markings; Moderate wear to covers; Library stamps to endpapers; Text pages clean & unmarked; Good binding with straight spine; Dark green covers with title in white lettering; 393 pages; "Stochastic Modelling and Control (Monographs on Statistics and Applied Probability)," by Mark Davis.
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Stochastic Modelling and Control
Published by Springer Netherlands, Springer Netherlands Feb 2012, 2012
ISBN 10: 9401086400 ISBN 13: 9789401086400
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
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£ 47.18
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 408 pp. Englisch.
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Stochastic Modelling and Control
Published by Springer Netherlands Feb 2012, 2012
ISBN 10: 9401086400 ISBN 13: 9789401086400
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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£ 75.47
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory. 408 pp. Englisch.
