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
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.
(17889 views)
Neural Fuzzy Systemsby Robert Fuller - Abo Akademi University
This text covers inference mechanisms in fuzzy expert systems, learning rules of feedforward multi-layer supervised neural networks, Kohonen's unsupervised learning algorithm for classification of input patterns, and fuzzy neural hybrid systems.
(13556 views)
Neural Network Designby 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.
(11736 views)
Recurrent Neural Networksby 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.
(13792 views)