Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland, 2018
ISBN 10: 3319867504 ISBN 13: 9783319867502
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 60,98
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification,to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered.'Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function.'Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego'This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. ' Bruno B. Averbeck.
Librería: preigu, Osnabrück, Alemania
EUR 56,70
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Advanced Data Analysis in Neuroscience | Integrating Statistical and Computational Models | Daniel Durstewitz | Taschenbuch | xxv | Englisch | 2018 | Springer | EAN 9783319867502 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 122,05
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: New. New. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 51,83
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland Aug 2018, 2018
ISBN 10: 3319867504 ISBN 13: 9783319867502
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 60,98
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is intended for use in advanced graduate courses in statistics / machine learning, as well as for all experimental neuroscientists seeking to understand statistical methods at a deeper level, and theoretical neuroscientists with a limited background in statistics. It reviews almost all areas of applied statistics, from basic statistical estimation and test theory, linear and nonlinear approaches for regression and classification,to model selection and methods for dimensionality reduction, density estimation and unsupervised clustering. Its focus, however, is linear and nonlinear time series analysis from a dynamical systems perspective, based on which it aims to convey an understanding also of the dynamical mechanisms that could have generated observed time series. Further, it integrates computational modeling of behavioral and neural dynamics with statistical estimation and hypothesis testing. This way computational models in neuroscience are not only explanatory frameworks, but become powerful, quantitative data-analytical tools in themselves that enable researchers to look beyond the data surface and unravel underlying mechanisms. Interactive examples of most methods are provided through a package of MatLab routines, encouraging a playful approach to the subject, and providing readers with a better feel for the practical aspects of the methods covered.'Computational neuroscience is essential for integrating and providing a basis for understanding the myriads of remarkable laboratory data on nervous system functions. Daniel Durstewitz has excellently covered the breadth of computational neuroscience from statistical interpretations of data to biophysically based modeling of the neurobiological sources of those data. His presentation is clear, pedagogically sound, and readily useable by experts and beginners alike. It is a pleasure to recommend this very well crafted discussion to experimental neuroscientists as well as mathematically well versed Physicists. The book acts as a window to the issues, to the questions, and to the tools for finding the answers to interesting inquiries about brains and how they function.'Henry D. I. Abarbanel Physics and Scripps Institution of Oceanography, University of California, San Diego'This book delivers a clear and thorough introduction to sophisticated analysis approaches useful in computational neuroscience. The models described and the examples provided will help readers develop critical intuitions into what the methods reveal about data. The overall approach of the book reflects the extensive experience Prof. Durstewitz has developed as a leading practitioner of computational neuroscience. ' Bruno B. Averbeck 320 pp. Englisch.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 90,46
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por Springer International Publishing, 2018
ISBN 10: 3319867504 ISBN 13: 9783319867502
Librería: moluna, Greven, Alemania
EUR 53,22
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Designed for use as a textbook in statistics for students from the neuro- and biosciences Integrates statistical analysis with a dynamical systems perspective and computational modelingReviews almost all areas of applied stati.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Aug 2018, 2018
ISBN 10: 3319867504 ISBN 13: 9783319867502
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 60,98
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Designed for use as a textbook in statistics for students from the neuro- and biosciencesIntegrates statistical analysis with a dynamical systems perspective and computational modelingReviews almost all areas of applied statistics, including advanced topics for computational neuroscientistsProvides interactive examples and MATLAB-based example codesSpringer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 320 pp. Englisch.