Encyclopedia of Computational Neuroscience
by Eugene M. Izhikevich, at al.
Publisher: Scholarpedia 2009
Neuroscience, Electrophysiology, Neuron, Network Dynamics, Brain Models, Synapse, Memory, Conditioning, Consciousness, Vision, Olfaction, Neuroimaging, Dynamical Systems, Oscillators, Synchronization, Pattern Formation, Chaos, Bifurcations, Simulation Environment, and more.
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by Kenji Suzuki (ed.) - InTech
Artificial neural networks may be the single most successful technology in the last two decades. The purpose of this book is to provide recent advances in architectures, methodologies, and applications of artificial neural networks.
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 William Bialek - arXiv
We all are fascinated by the phenomena of intelligent behavior, as generated by our own brains. As physicists we want to understand if there are some general principles that govern the dynamics of the neural circuits that underlie these phenomena.
by B. Mehlig - arXiv.org
These are lecture notes for my course on Artificial Neural Networks. This course describes the use of neural networks in machine learning: deep learning, recurrent networks, and other supervised and unsupervised machine-learning algorithms.