Time-Space, Spiking Neural Networks and Brain-Inspired Artificial Intelligence (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Springer Series on Bio- and Neurosystems, 7
Release date:	September 2018
First published:	2019
Authors:	Nikola K. Kasabov
Dimensions:	235 x 155 x 48mm (L x W x T)
Format:	Hardcover
Pages:	738
Edition:	1st ed. 2019
ISBN-13:	978-3-662-57713-4
Categories:	Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > Neurosciences Books > Computing & IT > Applications of computing > Artificial intelligence > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > Robotics Promotions
LSN:	3-662-57713-5
Barcode:	9783662577134

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