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XX, 254 p. Softcover. Versand aus Deutschland / We dispatch from Germany via Air Mail. Einband bestoßen, daher Mängelexemplar gestempelt, sonst sehr guter Zustand. Imperfect copy due to slightly bumped cover, apart from this in very good condition. Stamped. LNM 2064. Stamped. Lecture notes in mathematics, 2064; Mathematical biosciences subseries. Sprache: Englisch.
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Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics, 2006
ISBN 10: 0898716179 ISBN 13: 9780898716177
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Brossura. Zustand: fine. 2012; br., pp. 224, cm 24x16. Libro.
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Sprache: Englisch
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg, 2012
ISBN 10: 3642328814 ISBN 13: 9783642328817
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data.Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited.
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Taschenbuch. Zustand: Neu. Mathematical Modeling and Validation in Physiology | Applications to the Cardiovascular and Respiratory Systems | Jerry J. Batzel (u. a.) | Taschenbuch | Lecture Notes in Mathematics | xx | Englisch | 2012 | Springer | EAN 9783642328817 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Verlag: Society for Industrial & Applied Mathematics,U.S., 2006
ISBN 10: 0898716179 ISBN 13: 9780898716177
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Taschenbuch. Zustand: Neu. Stochastic Biomathematical Models | with Applications to Neuronal Modeling | Mostafa Bachar (u. a.) | Taschenbuch | Lecture Notes in Mathematics | xvi | Englisch | 2012 | Springer | EAN 9783642321566 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Society for Industrial and Applied Mathematics (SIAM), 2006
ISBN 10: 0898716179 ISBN 13: 9780898716177
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ISBN 10: 3642321569 ISBN 13: 9783642321566
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and itsapplication in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.
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In den WarenkorbPaperback. Zustand: Brand New. illustrated edition. 274 pages. 9.90x7.00x0.70 inches. In Stock.
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Verlag: Society for Industrial & Applied Mathematics,U.S., 2007
ISBN 10: 0898716179 ISBN 13: 9780898716177
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Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Stochastic biomathematical models are becoming increasingly important as new light is shed on the role of noise in living systems. In certain biological systems, stochastic effects may even enhance a signal, thus providing a biological motivation for the noise observed in living systems. Recent advances in stochastic analysis and increasing computing power facilitate the analysis of more biophysically realistic models, and this book provides researchers in computational neuroscience and stochastic systems with an overview of recent developments. Key concepts are developed in chapters written by experts in their respective fields. Topics include: one-dimensional homogeneous diffusions and their boundary behavior, large deviation theory and itsapplication in stochastic neurobiological models, a review of mathematical methods for stochastic neuronal integrate-and-fire models, stochastic partial differential equation models in neurobiology, and stochastic modeling of spreading cortical depression.
Sprache: Englisch
Verlag: Society for Industrial & Applied Mathematics,U.S., 2007
ISBN 10: 0898716179 ISBN 13: 9780898716177
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In den WarenkorbZustand: New. Print on Demand pp. 280 83 Illus. (34 Col.).
Sprache: Englisch
Verlag: Springer Berlin Heidelberg, Springer Berlin Heidelberg Dez 2012, 2012
ISBN 10: 3642328814 ISBN 13: 9783642328817
Anbieter: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Deutschland
Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This volume synthesizes theoretical and practical aspects of both the mathematical and life science viewpoints needed for modeling of the cardiovascular-respiratory system specifically and physiological systems generally. Theoretical points include model design, model complexity and validation in the light of available data, as well as control theory approaches to feedback delay and Kalman filter applications to parameter identification. State of the art approaches using parameter sensitivity are discussed for enhancing model identifiability through joint analysis of model structure and data.Practical examples illustrate model development at various levels of complexity based on given physiological information. The sensitivity-based approaches for examining model identifiability are illustrated by means of specific modeling examples. The themes presented address the current problem of patient-specific model adaptation in the clinical setting, where data is typically limited. 280 pp. Englisch.