A Brief Introduction to Neural Networks
by David Kriesel
Publisher: dkriesel.com 2011
Number of pages: 244
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.
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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 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 Todd Troyer - University of Texas at San Antonio
These notes have three main objectives: to present the major concepts of computational neuroscience, to present the basic mathematics that underlies these concepts, and to give the reader some idea of common approaches taken by neuroscientists.
by Mark Watson - Lulu.com
The book uses the author's libraries and the best of open source software to introduce AI (Artificial Intelligence) technologies like neural networks, genetic algorithms, expert systems, machine learning, and NLP (natural language processing).