Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 94,59
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
EUR 103,21
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 118,80
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 117,51
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New. In.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 117,50
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: New.
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
EUR 125,59
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: As New. Unread book in perfect condition.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 147,39
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 153,31
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: Brand New. 200 pages. 9.25x6.10x9.21 inches. In Stock.
Librería: preigu, Osnabrück, Alemania
EUR 95,25
Cantidad disponible: 5 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Probabilistic Spiking Neuronal Nets | Neuromathematics for the Computer Era | Antonio Galves (u. a.) | Taschenbuch | Lecture Notes on Mathematical Modelling in the Life Sciences | xv | Englisch | 2024 | Springer | EAN 9783031684081 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Idioma: Inglés
Publicado por Springer International Publishing, Springer Nature Switzerland, 2024
ISBN 10: 3031684087 ISBN 13: 9783031684081
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a self-contained introduction to a new class of stochastic models for systems of spiking neurons. These systems have a large number of interacting components, each one evolving as a stochastic process with a memory of variable length. Several mathematical tools are put to use, such as Markov chains, stochastic chains having memory of variable length, point processes having stochastic intensity, Hawkes processes, random graphs, mean field limits, perfect sampling algorithms, the Context algorithm, and statistical model selection.The book's focus on mathematically tractable objects distinguishes it from other texts on theoretical neuroscience. The biological complexity of neurons is not ignored, but reduced to some of its main features, such as the intrinsic randomness of neuronal dynamics. This reduction in complexity aims at explaining and reproducing statistical regularities and collective phenomena that are observed in experimental data, an approach that leads to mathematically rigorous results. With an emphasis on a constructive and algorithmic point of view, this book is directed towards mathematicians interested in learning about stochastic network models and their neurobiological underpinning, and neuroscientists interested in learning how to build and prove results with mathematical models that relate to actual experimental settings.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 86,24
Cantidad disponible: Más de 20 disponibles
Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer, Berlin, Springer International Publishing, Springer, 2024
ISBN 10: 3031684087 ISBN 13: 9783031684081
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 106,99
Cantidad disponible: 2 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book provides a self-contained introduction to a new class of stochastic models for systems of spiking neurons. These systems have a large number of interacting components, each one evolving as a stochastic process with a memory of variable length. Several mathematical tools are put to use, such as Markov chains, stochastic chains having memory of variable length, point processes having stochastic intensity, Hawkes processes, random graphs, mean field limits, perfect sampling algorithms, the Context algorithm, and statistical model selection.The book's focus on mathematically tractable objects distinguishes it from other texts on theoretical neuroscience. The biological complexity of neurons is not ignored, but reduced to some of its main features, such as the intrinsic randomness of neuronal dynamics. This reduction in complexity aims at explaining and reproducing statistical regularities and collective phenomena that are observed in experimental data, an approach that leads to mathematically rigorous results. With an emphasis on a constructive and algorithmic point of view, this book is directed towards mathematicians interested in learning about stochastic network models and their neurobiological underpinning, and neuroscientists interested in learning how to build and prove results with mathematical models that relate to actual experimental settings. 199 pp. Englisch.
Librería: moluna, Greven, Alemania
EUR 93,00
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.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 154,19
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 154,70
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Okt 2024, 2024
ISBN 10: 3031684087 ISBN 13: 9783031684081
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 106,99
Cantidad disponible: 1 disponibles
Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book provides a self-contained introduction to a new class of stochastic models for systems of spiking neurons. These systems have a large number of interacting components, each one evolving as a stochastic process with a memory of variable length. Several mathematical tools are put to use, such as Markov chains, stochastic chains having memory of variable length, point processes having stochastic intensity, Hawkes processes, random graphs, mean field limits, perfect sampling algorithms, the Context algorithm, and statistical model selection.The book¿s focus on mathematically tractable objects distinguishes it from other texts on theoretical neuroscience. The biological complexity of neurons is not ignored, but reduced to some of its main features, such as the intrinsic randomness of neuronal dynamics. This reduction in complexity aims at explaining and reproducing statistical regularities and collective phenomena that are observed in experimental data, an approach that leads to mathematically rigorous results.With an emphasis on a constructive and algorithmic point of view, this book is directed towards mathematicians interested in learning about stochastic network models and their neurobiological underpinning, and neuroscientists interested in learning how to build and prove results with mathematical models that relate to actual experimental settings.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 216 pp. Englisch.