Recurrent Neural Networks
by Xiaolin Hu, P. Balasubramaniam
Publisher: InTech 2008
Number of pages: 400
The concept of neural network originated from neuroscience, and one of its primitive aims is to help us understand the principle of the central nerve system and related behaviors through mathematical modeling. The first part of the book is a collection of three contributions dedicated to this aim.
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by Martin T. Hagan, et al.
This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules. In it, the authors emphasize a coherent presentation of the principal neural networks, methods for training them and their applications.
by Ivan F Wilde - King's College London
These notes are based on lectures given in the Mathematics Department at King's College London. An attempt has been made to present a logical (mathematical) account of some of the basic ideas of the 'artificial intelligence' aspects of the subject.
by Eugene M. Izhikevich, at al. - Scholarpedia
Neuroscience, Electrophysiology, Neuron, Network Dynamics, Brain Models, Synapse, Memory, Conditioning, Consciousness, Vision, Olfaction, Neuroimaging, Dynamical Systems, Oscillators, Synchronization, Pattern Formation, Chaos, Bifurcations, etc.
by David Kriesel - dkriesel.com
Text and illustrations should be memorable and easy to understand to offer as many people as possible access to the field of neural networks. The chapters are individually accessible to readers with little previous knowledge.