1 / 12

Introduction to Neural Networks

Introduction to Neural Networks. Recurrent Neural Networks. Recurrent Neural Networks. Recurrent neural networks are neural networks with feedback loops. Why recurrent neural networks? – A new approach to problem solving (via neurodynamics).

karim
Download Presentation

Introduction to Neural Networks

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Introduction to Neural Networks Recurrent Neural Networks

  2. Recurrent Neural Networks • 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 xk:

  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.

More Related