Branch : Electrical and Electronics Engineering | Subject : Neural Networks and Fuzzy Logic

• Introduction to Neural Networks

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• History of neural networks

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• Network architectures

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• Artificial Intelligence of neural network

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• Knowledge Representation

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• Human Brain

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• Model of a neuron

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• Neural Network as a Directed Graph

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• The concept of time in neural networks

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• Components of neural Networks

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• Network Topologies

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• The bias neuron

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• Representing neurons

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• Order of activation

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• Introduction to learning process

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• Paradigms of learning

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• Training patterns and Teaching input

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• Using training samples

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• Learning curve and error measurement

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• Gradient optimization procedures

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• Exemplary problems allow for testing self-coded learning strategies

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• Hebbian learning rule

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• Genetic Algorithms

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• Expert systems

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• Fuzzy Systems for Knowledge Engineering

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• Neural Networks for Knowledge Engineering

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• Feed-forward Networks

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• Components and structure of an RBF network

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• Comparing RBF networks and multilayer perceptrons

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