ppt on ARTIFICIAL NEURAL NETWORKS.pdf | seminor topic free download |

PAPERS ON ARTIFICIAL NEURAL NETWORKS::

Abstract

This report is an introduction to Artificial Neural Networks. The various types of neural
networks are explained and demonstrated, applications of neural networks like ANNs in
medicine are described, and a detailed historical background is provided. The connection
between the artificial and the real thing is also investigated and explained. Finally, the
mathematical models involved are presented and demonstrated.

Contents:

1. Introduction to Neural Networks

1.1 What is a neural network?
1.2 Historical background
1.3 Why we use neural networks?
1.4 Neural networks versus conventional computers - a

comparison

2. Human and Artificial Neurones - investigating the similarities

2.1 How the Human Brain Learns?
2.2 From Human Neurones to Artificial Neurones

3. An Engineering approach

3.1 A simple neuron - description of a simple neuron
3.2 Firing rules - How neurones make decisions
3.3 A more complicated neuron

4. Architecture of neural networks

4.1 Feed-forward (associative) networks
4.2 Feedback (autoassociative) networks
4.3 Recurrent networks
4.4 Hopfield networks
4.5 Stochastic neural networks
4.6Modular neural networks
4.7 Network layers

5. The Learning Process

5.1Transfer Function
5.2The Back-Propagation Algorithm
6. Applications of neural networks

Click here to download