Abstract
Brain and Classical Neural Networks gives a modern review of classical neurodynamics, including brain physiology, biological and artificial neural networks, synchronization, spike neural nets and wavelet resonance, motor control and learning. It includes the following sections:
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2.1
Human Brain
This section presents the basics of Basics of Brain Physiology necessary for comprehensive reading of the book.
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2.2
Biological versus Artificial Neural Networks
This section reviews standard models of artificial neural networks and contrasts them with biophysical models of neural ensembles.
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2.3
Synchronization in Neurodynamics
This section elaborates on the important concept of synchronization in coupled chaotic oscillators, neural dynamical systems, and Kuramoto-type models, using methods based on Lyapunov exponents.
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2.4
Spike Neural Networks and Wavelet Resonance
This section presents wavelet-based neural-ensemble dynamics in general and in epileptic spikes in particular.
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2.5
Human Motor Control and Learning
This section presents basics of human neuro-motor control, memory, and motor learning and cerebellar muscular synergy.
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© 2010 Springer Science+Business Media B.V.
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Ivancevic, V.G., Ivancevic, T.T. (2010). Brain and Classical Neural Networks. In: Quantum Neural Computation. Intelligent Systems, Control and Automation: Science and Engineering, vol 40. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-3350-5_2
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DOI: https://doi.org/10.1007/978-90-481-3350-5_2
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Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-3349-9
Online ISBN: 978-90-481-3350-5
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