Author: Nikola K. Kasabov
Publisher: Springer
ISBN: 3662577151
Category : Technology & Engineering
Languages : en
Pages : 742
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Book Description
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.
Author: Răzvan V. Florian (Doctorat în informatică.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 204
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Book Description
Author: Chris Eliasmith
Publisher: Oxford University Press
ISBN: 0199794693
Category : Psychology
Languages : en
Pages : 475
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Book Description
How to Build a Brain provides a detailed exploration of a new cognitive architecture - the Semantic Pointer Architecture - that takes biological detail seriously, while addressing cognitive phenomena. Topics ranging from semantics and syntax, to neural coding and spike-timing-dependent plasticity are integrated to develop the world's largest functional brain model.
Author: Guoqi Li
Publisher: Frontiers Media SA
ISBN: 2889637670
Category :
Languages : en
Pages : 234
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Book Description
Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 9780521890793
Category : Computers
Languages : en
Pages : 498
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Book Description
Neurons in the brain communicate by short electrical pulses, the so-called action potentials or spikes. How can we understand the process of spike generation? How can we understand information transmission by neurons? What happens if thousands of neurons are coupled together in a seemingly random network? How does the network connectivity determine the activity patterns? And, vice versa, how does the spike activity influence the connectivity pattern? These questions are addressed in this 2002 introduction to spiking neurons aimed at those taking courses in computational neuroscience, theoretical biology, biophysics, or neural networks. The approach will suit students of physics, mathematics, or computer science; it will also be useful for biologists who are interested in mathematical modelling. The text is enhanced by many worked examples and illustrations. There are no mathematical prerequisites beyond what the audience would meet as undergraduates: more advanced techniques are introduced in an elementary, concrete fashion when needed.
Author: Sergio Davies
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: David Sterratt
Publisher: Cambridge University Press
ISBN: 1108483143
Category : Science
Languages : en
Pages : 553
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Book Description
Learn to use computational modelling techniques to understand the nervous system at all levels, from ion channels to networks.
Author: Steve Furber
Publisher: NowOpen
ISBN: 9781680836523
Category :
Languages : en
Pages : 352
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Book Description
This books tells the story of the origins of the world's largest neuromorphic computing platform, its development and its deployment, and the immense software development effort that has gone into making it openly available and accessible to researchers and students the world over
Author: Yoshua Bengio
Publisher: Now Publishers Inc
ISBN: 1601982941
Category : Computational learning theory
Languages : en
Pages : 145
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Book Description
Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
Author: Wulfram Gerstner
Publisher: Cambridge University Press
ISBN: 1107060834
Category : Computers
Languages : en
Pages : 591
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Book Description
This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.
