ARTIFICIAL NEURAL NETWORKS

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Contents

• Introduction

• Concepts:
• Biological Type Neural Networks.
• Application driven Neural Networks.
• Taxonomy of Artificial Neural Networks.
• Supervised and Unsupervised Artificial Neural Networks.
• Basis function and Activation function.
• Structures of Neural Networks.
• Applications.
• Unsupervised Models:
• Fixed weight Associative Memory Networks.
• Competitive Learning Networks.
• Supervised Models:
• Decision Based Neural Networks.
• Aproximation/Optimization Neural Networks.
• Example.
• Bibliography.

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Artificial Neural Networks