An Introduction to Neural Networks
by Ben Krose, Patrick van der Smagt
Number of pages: 135
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.
Download or read it online for free here:
by Jeff Heaton - Heaton Research
The book is an introduction to Neural Networks and Artificial Intelligence. Neural network architectures, such as the feedforward, Hopfield, and self-organizing map architectures are discussed. Training techniques are also introduced.
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 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.
by Xiaolin Hu, P. Balasubramaniam - InTech
The concept of neural network originated from neuroscience, and one of its aims is to help us understand the principle of the central nerve system through mathematical modeling. The first part of the book is dedicated to this aim.