| 書目名稱 | The Relevance of the Time Domain to Neural Network Models |
| 編輯 | A. Ravishankar Rao,Guillermo A. Cecchi |
| 視頻video | http://file.papertrans.cn/919/918429/918429.mp4 |
| 概述 | The book concentrates on a crucial aspect of brain modeling: the nature and functional relevance of temporal interactions in neural systems.Develops a unified view of how the time domain can be effect |
| 叢書名稱 | Springer Series in Cognitive and Neural Systems |
| 圖書封面 |  |
| 描述 | .A significant amount of effort in neural modeling is directed towards understanding the representation of information in various parts of the brain, such as cortical maps [6], and the paths along which sensory information is processed. Though the time domain is integral an integral aspect of the functioning of biological systems, it has proven very challenging to incorporate the time domain effectively in neural network models. A promising path that is being explored is to study the importance of synchronization in biological systems. Synchronization plays a critical role in the interactions between neurons in the brain, giving rise to perceptual phenomena, and explaining multiple effects such as visual contour integration, and the separation of superposed inputs...The purpose of this book is to provide a unified view of how the time domain can be effectively employed in neural network models. A first direction to consider is to deploy oscillators that model temporal firing patterns of a neuron or a group of neurons. There is a growing body of research on the use of oscillatory neural networks, and their ability to synchronize under the right conditions. Such networks of synchroni |
| 出版日期 | Book 2012 |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-1-4614-0724-9 |
| isbn_softcover | 978-1-4614-2992-0 |
| isbn_ebook | 978-1-4614-0724-9Series ISSN 2363-9105 Series E-ISSN 2363-9113 |
| issn_series | 2363-9105 |
| copyright | Springer Science+Business Media, LLC 2012 |
|Archiver|手機版|小黑屋|
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