| 書目名稱 | Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence | | 編輯 | Nikola K. Kasabov | | 視頻video | http://file.papertrans.cn/926/925561/925561.mp4 | | 概述 | Presents background knowledge and new generic methods for spiking neural networks, evolving spiking neural networks and brain-inspired spiking neural networks.Describes new specific methods for the cr | | 叢書名稱 | Springer Series on Bio- and Neurosystems | | 圖書封面 |  | | 描述 | .Spiking neural networks (SNN) are biologically inspired computational models that represent and process information internally as trains of spikes. This monograph book presents the classical theory and applications of SNN, including original author’s contribution to the area. The book introduces for the first time not only deep learning and deep knowledge representation in the human brain and in brain-inspired SNN, but takes that further to develop new types of AI systems, called in the book brain-inspired AI (BI-AI).? BI-AI systems are illustrated on: cognitive brain data, including EEG, fMRI and DTI; audio-visual data; brain-computer interfaces; personalized modelling in bio-neuroinformatics; multisensory streaming data modelling in finance, environment and ecology; data compression; neuromorphic hardware implementation. Future directions, such as the integration of multiple modalities, such as quantum-, molecular- and brain information processing, is presented in the last chapter. The book is a research book for postgraduate students, researchers and practitioners across wider areas, including computer and information sciences, engineering, applied mathematics, bio- and neurosc | | 出版日期 | Book 2019 | | 關(guān)鍵詞 | Deep knowledge representation; Integration of human intelligence and artificial intelligence; Deep lea | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-662-57715-8 | | isbn_softcover | 978-3-662-58607-5 | | isbn_ebook | 978-3-662-57715-8Series ISSN 2520-8535 Series E-ISSN 2520-8543 | | issn_series | 2520-8535 | | copyright | Springer-Verlag GmbH Germany, part of Springer Nature 2019 |
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