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 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.
by Ben Goertzel - Plenum Press
This text applies the concepts of complexity science to provide an explanation of all aspects of human creativity. The book describes the model that integrates ideas from computer science, mathematics, neurobiology, philosophy, and psychology.
by Kenji Suzuki - InTech
The purpose of this book is to provide recent advances of artificial neural networks in biomedical applications. The target audience includes professors and students in engineering and medical schools, medical doctors, healthcare professionals, etc.
by Allessandro Treves, Yasser Roudi - SISSA
We review the common themes, the network models and the mathematical formalism underlying our studies about different stages in the evolution of the human brain. These studies discuss the evolution of cortical networks in terms of their computations.