Items related to Form Versus Function: Theory and Models for Neuronal...
Synopsis
This thesis addresses one of the most fundamental challenges for modern science: how can the brain as a network of neurons process information, how can it create and store internal models of our world, and how can it infer conclusions from ambiguous data? The author addresses these questions with the rigorous language of mathematics and theoretical physics, an approach that requires a high degree of abstraction to transfer results...
About the Author
Mihai Petrovici started studying Physics at the University of Heidelberg in 2001. During his early undergraduate days, he worked on particle tracking for the ALICE experiment at CERN. For his diploma thesis, he moved to solid state physics, where he studied glasses at low temperatures. He began his PhD in 2008 in the Electronic Vision(s) group of Karlheinz Meier and Johannes Schemmel, where he worked at the...
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2016
- ISBN 10 3319395513
- ISBN 13 9783319395517
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages400
Search results for Form Versus Function: Theory and Models for Neuronal...
Stock Image
Form Versus Function: Theory and Models for Neuronal Substrates (Springer Theses)
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # ABLIING23Mar3113020096942
Quantity: Over 20 available
Stock Image
Form Versus Function: Theory and Models for Neuronal Substrates (Springer Theses)
Seller: California Books, Miami, FL, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # I-9783319395517
Quantity: Over 20 available
Stock Image
Form Versus Function: Theory and Models for Neuronal Substrates (Springer Theses)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In English. Seller Inventory # ria9783319395517_new
Quantity: Over 20 available
Seller Image
Form Versus Function: Theory and Models for Neuronal Substrates
Published by
Springer International Publishing Jul 2016, 2016
ISBN 10: 3319395513
ISBN 13: 9783319395517
New
Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis addresses one of the most fundamental challenges for modern science: how can the brain as a network of neurons process information, how can it create and store internal models of our world, and how can it infer conclusions from ambiguous data The author addresses these questions with the rigorous language of mathematics and theoretical physics, an approach that requires a high degree of abstraction to transfer results of wet lab biology to formal models.The thesis starts with an in-depth description of the state-of-the-art in theoretical neuroscience, which it subsequently uses as a basis to develop several new and original ideas. Throughout the text, the author connects the form and function of neuronal networks. This is done in order to achieve functional performance of biological brains by transferring their form to synthetic electronics substrates, an approach referred to as neuromorphic computing. The obvious aspect that this transfer can never be perfect but necessarily leads to performance differences is substantiated and explored in detail.The author also introduces a novel interpretation of the firing activity of neurons. He proposes a probabilistic interpretation of this activity and shows by means of formal derivations that stochastic neurons can sample from internally stored probability distributions. This is corroborated by the author's recent findings, which confirm that biological features like the high conductance state of networks enable this mechanism. The author goes on to show that neural sampling can be implemented on synthetic neuromorphic circuits, paving the way for future applications in machine learning and cognitive computing, for example as energy-efficient implementations of deep learning networks.The thesis offers an essential resource for newcomers to the field and an inspiration for scientists working in theoretical neuroscience and the future of computing. 400 pp. Englisch. Seller Inventory # 9783319395517
Quantity: 2 available
Seller Image
Form Versus Function: Theory and Models for Neuronal Substrates
Published by
Springer International Publishing, 2016
ISBN 10: 3319395513
ISBN 13: 9783319395517
New
Hardcover
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This thesis addresses one of the most fundamental challenges for modern science: how can the brain as a network of neurons process information, how can it create and store internal models of our world, and how can it infer conclusions from ambiguous data The author addresses these questions with the rigorous language of mathematics and theoretical physics, an approach that requires a high degree of abstraction to transfer results of wet lab biology to formal models.The thesis starts with an in-depth description of the state-of-the-art in theoretical neuroscience, which it subsequently uses as a basis to develop several new and original ideas. Throughout the text, the author connects the form and function of neuronal networks. This is done in order to achieve functional performance of biological brains by transferring their form to synthetic electronics substrates, an approach referred to as neuromorphic computing. The obvious aspect that this transfercan never be perfect but necessarily leads to performance differences is substantiated and explored in detail.The author also introduces a novel interpretation of the firing activity of neurons. He proposes a probabilistic interpretation of this activity and shows by means of formal derivations that stochastic neurons can sample from internally stored probability distributions. This is corroborated by the author's recent findings, which confirm that biological features like the high conductance state of networks enable this mechanism. The author goes on to show that neural sampling can be implemented on synthetic neuromorphic circuits, paving the way for future applications in machine learning and cognitive computing, for example as energy-efficient implementations of deep learning networks.The thesis offers an essential resource for newcomers to the field and an inspiration for scientists working in theoretical neuroscience and the future of computing. Seller Inventory # 9783319395517
Quantity: 1 available
Seller Image
Form Versus Function: Theory and Models for Neuronal Substrates
Published by
Springer International Publishing, 2016
ISBN 10: 3319395513
ISBN 13: 9783319395517
New
Hardcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated as an outstanding PhD thesis by Heidelberg University, GermanyProvides an excellent state-of-the-art overview of theoretical neuroscienceAn inspiration for newcomers to engage in this fascinating and f. Seller Inventory # 120395793
Quantity: Over 20 available
Stock Image
Form Versus Function: Theory and Models for Neuronal Substrates
Seller: Revaluation Books, Exeter, United Kingdom
Seller rating 5 out of 5 stars
Hardcover. Condition: Brand New. 374 pages. 9.25x6.10x1.18 inches. In Stock. Seller Inventory # x-3319395513
Quantity: 2 available
Stock Image
Form Versus Function: Theory and Models for Neuronal Substrates (Springer Theses)
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
Hardcover. Condition: Like New. Like New. book. Seller Inventory # ERICA77333193955136
Quantity: 1 available