Terman david h (27 resultados)

Condición: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.

hardcover. Condición: Very Good. Estado de la sobrecubierta: N/A.

hardcover. Condición: As New. Used, hardcover like new. Sharp, square, clean, fresh & serviceable copy. No highlighting, marginalia or page tears.

Condición: New.

Condición: New. In English.

paperback. Condición: New. In shrink wrap. Looks like an interesting title.

Condición: New.

Condición: New.

Condición: New. In English.

Condición: New. pp. 440.

Condición: New.

Condición: New. pp. xv + 422.

Paperback. Condición: Brand New. 2010 edition. 437 pages. 9.13x6.13x0.92 inches. In Stock.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.…

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.…

Condición: As New. Unread book in perfect condition.

Paperback. Condición: Like New. Like New. book.

Condición: As New. Unread book in perfect condition.

Condición: gut. Mathematical Foundations of Neuroscience (Interdisciplinary Applied Mathematics, 35, Band 35) In englischer Sprache. pages.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This volume introduces some basic theories on computational neuroscience. Chapter 1 is a brief introduction to neurons, tailored to the subsequent chapters. Chapter 2 is a self-contained introduction to dynamical systems and bifurcation theory, oriented tow.…

Condición: New. Print on Demand pp. 440 38 Illus. (Col.).

Condición: New. PRINT ON DEMAND pp. 440.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Key authorsLinks both neuroscience and applied mathematicsExtensive illustrations, examples and exercises using real dataThis book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical app.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Key authorsLinks both neuroscience and applied mathematicsExtensive illustrations, examples and exercises using real dataThis book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical app.…

Condición: New. Print on Demand pp. xv + 422 38 Illus. (Col.).

Condición: New. PRINT ON DEMAND pp. xv + 422.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book applies methods from nonlinear dynamics to problems in neuroscience. It uses modern mathematical approaches to understand patterns of neuronal activity seen in experiments and models of neuronal behavior. The intended audience is researchers interested in applying mathematics to important problems in neuroscience, and neuroscientists who would like to understand how to create models, as well as the mathematical and computational methods for analyzing them. The authors take a very broad approach and use many different methods to solve and understand complex models of neurons and circuits. They explain and combine numerical, analytical, dynamical systems and perturbation methods to produce a modern approach to the types of model equations that arise in neuroscience. There are extensive chapters on the role of noise, multiple time scales and spatial interactions in generating complex activity patterns found in experiments. The early chapters require little more than basic calculus and some elementary differential equations and can form the core of a computational neuroscience course. Later chapters can be used as a basis for a graduate class and as a source for current research in mathematical neuroscience. The book contains a large number of illustrations, chapter summaries and hundreds of exercises which are motivated by issues that arise in biology, and involve both computation and analysis. Bard Ermentrout is Professor of Computational Biology and Professor of Mathematics at the University of Pittsburgh. David Terman is Professor of Mathematics at the Ohio State University.Springer Nature Customer Service Center GmbH, Europaplatz 3, 69115 Heidelberg 440 pp. Englisch.…