1 Introduction to Neural Networks Recurrent Neural Networks.

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Presentation transcript:

1 Introduction to Neural Networks Recurrent Neural Networks

2 Recurrent neural networks are neural networks with feedback loops. Why recurrent neural networks? –A new approach to problem solving (via neurodynamics). –A better way for long-term prediction (e.g., financial forecasting).

3 Hopfield Neural Networks (RNNs with fixed-points)

4 Hopfield Network Architecture

5 Hopfield Network Formulation

6 Hopfield Network for Pattern Associative Memory

7 Stability analysis

8 Trend of change in energy due to the change in state x k :

9 Recurrent Multilayer Perceptron

10 Recurrent Multilayer Perceptron Network Architecture

11 Formulation and Learning Algorithm

12 Main Applications of Hopfield Networks Pattern Association Optimisation Time-series modelling and prediction, with better performance than feedforward MLP.