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Artificial Neural Networks
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Artificial Neural Networks
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25 Questions

1. What's the significance of the cost function?

2. What are the similarities between biological neural networks and artificial neural networks?

3. In Oja's rule what's the limiting term and what does it do?

4. What are the characteristics of the learning constant?

5. What tasks are to be solved by an artificial neural network?

6. What is an epoch?

7. What is unsupervised learning?

8. How can artificial neural networks separate the feature space?

9. What are some applications of ANN?

10. State the competitive learning rule

11. Energy Minimization

12. State Oja's rule for unsupervised learning

13. What do artificial neurons and neural networks try to imitate?

14. Support Vector Learning

15. For MLPs and backprop and perhaps simple perceptrons how is the change in the weights determined?

16. State the Kohonen learning rule for neural networks

17. What is adaptive resonance theory?

18. What property relating to errors do we require of neural networks

19. For MCPs the new weight equals..?

20. How can the synaptic strength be modified in artificial neural networks?

21. What is ANN inspired by?

22. Examples of feed forward networks

23. What is neural computing?

24. What is the difference between MLP and RBF?

25. What is the ultimate objective of training?

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