Neural Networks
by Rolf Pfeifer, Dana Damian, Rudolf Fuchslin
Publisher: University of Zurich 2010
Number of pages: 111
Description:
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, non-supervised networks (competitive, Kohonen, Hebb), recurrent networks (Hopfield, CTRNNs - continuous-time recurrent neural networks), spiking neural networks, spike-time dependent plasticity, applications.
Download or read it online for free here:
Download link
(8.7MB, PDF)
Similar books
An Introduction to Neural Networksby 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.
(15104 views)
Neural Networks: A Systematic Introductionby Raul Rojas - Springer
A general theory of artificial neural nets. The book starts with the simple nets, and shows how the models change when more general computing elements and net topologies are introduced. Suitable as a basis for university courses in neurocomputing.
(17814 views)
Of the Evolution of the Brainby 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.
(12505 views)
Artificial Neural Networksby 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.
(5947 views)