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

• Main Author: Kasabov, Nikola K. (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Springer Series on Bio- and Neurosystems, 7
• Subjects: Computational intelligence.; Bioinformatics.; Neurosciences.; Robotics.; Automation.; Pattern recognition.; Computational Intelligence.; Computational Biology/Bioinformatics.; Robotics and Automation.; Pattern Recognition.

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 introduce...

Table of Contents:

• Part I. Time-Space and AI
• Part II. The Human Brain
• Part III. Spiking Neural Networks
• Part IV. SNN for Deep Learning and Deep Knowledge Representation of Brain Data
• Part V. SNN for Audio-Visual Data and Brain-Computer Interfaces
• Part VI. SNN in Bio- and Neuroinformatics
• Part VII. SNN for Deep in Time-Space Learning and Deep Knowledge Representation of Multisensory Streaming Data
• Part VIII. Future development in BI-SNN and BI-AI.