Brain and Classical Neural Networks

  • Vladimir G. IvancevicEmail author
  • Tijana T. Ivancevic
Part of the Intelligent Systems, Control and Automation: Science and Engineering book series (ISCA, volume 40)


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:

  1. 2.1

    Human Brain

    This section presents the basics of Basics of Brain Physiology necessary for comprehensive reading of the book.

  2. 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.

  3. 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.

  4. 2.4

    Spike Neural Networks and Wavelet Resonance

    This section presents wavelet-based neural-ensemble dynamics in general and in epileptic spikes in particular.

  5. 2.5

    Human Motor Control and Learning

    This section presents basics of human neuro-motor control, memory, and motor learning and cerebellar muscular synergy.



Purkinje Cell Discrete Wavelet Transform Wavelet Transform Stochastic Resonance Phase Synchronization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.Department of DefenceDefence Science & Technology Organisation (DSTO)EdinburghAustralia
  2. 2.School of Electrical & Information EngineeringUniversity of South AustraliaAdelaideAustralia

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