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 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 Rolf Pfeifer, Dana Damian, Rudolf Fuchslin - University of Zurich
Systematic introduction to neural networks, biological foundations; important network classes and learning algorithms; supervised models (perceptrons, adalines, multi-layer perceptrons), support-vector machines, echo-state networks, etc.
by Ben Krose, Patrick van der Smagt
This manuscript attempts to provide the reader with an insight in artificial neural networks. The choice of describing robotics and vision as neural network applications coincides with the neural network research interests of the authors.
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.