Verlag: Cambridge University Press, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
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ISBN 10: 1107428203 ISBN 13: 9781107428201
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In den WarenkorbPaperback. Zustand: new. Paperback. The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Cambridge University Press Apr 2015, 2015
ISBN 10: 1107428203 ISBN 13: 9781107428201
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ISBN 10: 1107428203 ISBN 13: 9781107428201
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In den WarenkorbHardcover. Zustand: new. Hardcover. The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, Cambridge, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
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In den WarenkorbHardcover. Zustand: new. Hardcover. The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 312 pages. 10.00x7.00x0.75 inches. In Stock.
Verlag: Cambridge University Press, Cambridge, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Hardcover. The mathematical theory of stochastic dynamics has become an important tool in the modeling of uncertainty in many complex biological, physical, and chemical systems and in engineering applications - for example, gene regulation systems, neuronal networks, geophysical flows, climate dynamics, chemical reaction systems, nanocomposites, and communication systems. It is now understood that these systems are often subject to random influences, which can significantly impact their evolution. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians and scientists. Starting from the knowledge base typical for beginning graduate students in applied mathematics, it introduces the basic tools from probability and analysis and then develops for stochastic systems the properties traditionally calculated for deterministic systems. The book's final chapter opens the door to modeling in non-Gaussian situations, typical of many real-world applications. Rich with examples, illustrations, and exercises with solutions, this book is also ideal for self-study. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty, from analytical, deterministic, structural and numerical perspectives. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: Cambridge University Press, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
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In den WarenkorbBuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - An accessible introduction for applied mathematicians to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty.
Verlag: Cambridge University Press, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
Sprache: Englisch
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ISBN 10: 1107428203 ISBN 13: 9781107428201
Sprache: Englisch
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In den WarenkorbZustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quant.
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In den WarenkorbHardcover. Zustand: Brand New. 1st edition. 312 pages. 10.00x7.00x0.75 inches. In Stock. This item is printed on demand.
Verlag: Cambridge University Press, 2015
ISBN 10: 1107075394 ISBN 13: 9781107075399
Sprache: Englisch
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ISBN 10: 1107075394 ISBN 13: 9781107075399
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In den WarenkorbGebunden. Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book serves as a concise introductory text on stochastic dynamics for applied mathematicians. Rich with examples, illustrations, and exercises with their solutions, it provides an accessible introduction to concepts and techniques for describing, quant.