| Document Type
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BL
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| Record Number
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882913
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| Main Entry
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Kasabov, Nikola K.
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| Title & Author
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Time-space, spiking neural networks and brain-inspired artificial intelligence /\ Nikola K. Kasabov.
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| Publication Statement
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Berlin :: Springer,, [2019]
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| Series Statement
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Springer series on bio- and neurosystems ;; volume 7
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| Page. NO
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1 online resource
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| ISBN
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3662577143
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: 3662577151
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: 366258607X
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: 9783662577141
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: 9783662577158
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: 9783662586075
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3662577135
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9783662577134
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| Contents
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Tim-space and AI articficial neural networks -- The human brain -- Spiking neural networks -- Deep learning and deep knowledge representation of brain data -- SNN for audio-visual data and brain-computer interfaces -- SNN inbio-and neuroinformatics -- Deep in tim-space learning and deep knowledge representation of multisensory streaming data -- Future development in BI-SNN and BI-AI.
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| Abstract
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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 neurosciences.
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| Subject
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Computational neuroscience.
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Machine learning.
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Neural networks (Computer science)
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Object-oriented methods (Computer science)
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Artificial intelligence.
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Computational neuroscience.
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COMPUTERS-- Programming-- Object Oriented.
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Life sciences: general issues.
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Machine learning.
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Neural networks (Computer science)
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Neurosciences.
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Object-oriented methods (Computer science)
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Pattern recognition.
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Robotics.
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| Dewey Classification
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005.117
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| LC Classification
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QA76.9.O35
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