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Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence

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  • 772 pages
  • 28 hours of reading

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Focusing on spiking neural networks (SNN), this monograph explores their classical theory and applications while introducing brain-inspired AI (BI-AI). It delves into deep learning and knowledge representation, showcasing BI-AI systems through various cognitive data types, including EEG and fMRI, as well as applications in brain-computer interfaces and multisensory data modeling. The final chapter discusses future directions, including the integration of diverse modalities in information processing. This research-oriented text is aimed at postgraduate students and professionals in multiple disciplines.

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Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence, Nikola K. Kasabov

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Released
2018
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(Hardcover)
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