NEURAL NETWORKS

Jun 21st, 2015
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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.

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NEURAL NETWORKS by Christos Stergiou and Dimitrios Siganos AbstractThis 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 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 Pattern recognition - an example 3.4 A more complicated neuron 4. Architecture of neural networks 4.1 Feed-forward (associative) networks 4.2 Feedback (autoassociative) networks 4.3 Network layers 4.4 Perceptrons 5. The Learning Process 5.1 Transfer Function 5.2 An Example to illustrate the above teaching procedure 5.3 The Back-Propagation Algorithm 6. Applications of neural networks 6.1 Neural networks in practice 6.2 Neural networks in medicine 6.2.1 Modelling and Diagnosing the Cardiovascular

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