| 书目名称 | Form Versus Function: Theory and Models for Neuronal Substrates |
| 编辑 | Mihai Alexandru Petrovici |
| 视频video | |
| 概述 | Nominated as an outstanding PhD thesis by Heidelberg University, Germany.Provides an excellent state-of-the-art overview of theoretical neuroscience.An inspiration for newcomers to engage in this fasc |
| 丛书名称 | Springer Theses |
| 图书封面 |  |
| 描述 | 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 inter |
| 出版日期 | Book 2016 |
| 关键词 | Theoretical Neuroscience; Computational Neuroscience; Neuromorphic Hardware; Neural Network Theory; Neur |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-39552-4 |
| isbn_softcover | 978-3-319-81913-6 |
| isbn_ebook | 978-3-319-39552-4Series ISSN 2190-5053 Series E-ISSN 2190-5061 |
| issn_series | 2190-5053 |
| copyright | Springer International Publishing Switzerland 2016 |
发表于 2025-3-21 19:33:56
