Topic 05 Neural Network

Topic: 05 Neural Network Questions

1. What is a neural network?

   [2017, 2016, 2015, 2011]

2. What is an artificial neural network (ANN)?

   [2021, 2018, 2012]

3. Draw an analogy between artificial neural networks and biological neural networks.

   [2021, 2019, 2012]

4. Give a simple mathematical model for a neuron.

   [2013]

5. Describe the working principles of an artificial neural network with a diagram.

   [2020, 2018, 2017, 2015, 2011]

   Or

   Mention the architecture of an artificial neural network.

   [2019]

6. Mention various types of learning paradigms in an ANN. Discuss any one.

   [2020, 2013]

   Or

   Mention the various types of learning paradigms in an ANN.

   [2018]

   Or

   Discuss the following learning situations of artificial neural networks:

   • Supervised learning
   • Unsupervised learning [2014] What is reinforcement learning? [2019, 2013]

7. Differentiate between supervised and unsupervised learning.

   [2020, 2018, 2017, 2015, 2011]

   Or

   Compare supervised learning and unsupervised learning.

   [2013]

   Or

   What are the differences between supervised and unsupervised learning?

   [2016]

8. Describe the McCulloch-Pitts artificial neuron model.

   [2021, 2016, 2012]

   Or

   Explain the McCulloch-Pitts neuron.

   [2020, 2018, 2014]

9. Discuss Rosenblatt’s perceptron learning algorithm.

   [2021]

10. Describe the single-layer feed-forward neural networks briefly.

    [2016]

11. Explain the multi-layer feed-forward neural network with an algorithm.

    [2014]

    Or

    Explain the backpropagation learning algorithm with an example.

    [2011]

    Or

    Write down the backpropagation algorithm.

    [2020, 2016]

    Or

    Explain the backpropagation learning algorithm in a multi-layer neural network.

    [2018, 2014, 2013]

12. Show the classification of learning algorithms used in neural networks.

    [2017]

13. Give the comparison of conventional and neural network computation.

    [2017]

14. What is perceptron? How does the perceptron learn?

    [2020, 2017, 2011]

15. Write the steps of the perceptron’s training algorithm.

    [2020, 2018, 2012]

16. Mention the weight updating rule in perceptron learning.

    [2014]

17. Explain why perceptron can learn the operations of AND, and OR but not XOR.

    [2019, 2018, 2015, 2012]

18. How do you solve XOR with a multilayer perceptron?

    [2021]

    Or

    State and explain XOR problem. Also, discuss how to overcome it.

    [2014]

19. Draw and explain the biological neuron.

    [2017, 2015]

20. What are the features of biological neural networks that make it superior to even the most sophisticated AI computer systems?

    [2014]

21. A 4-input neuron has weights 1, 2, 3, and 4. The transfer function is linear with the constant proportionality being equal to 2. The inputs are 4, 10, 5, and 20. What will be the output?

    [2017, 2013]

22. What do you mean by learning and recall?

    [2011]

23. Discuss the following learning situations of artificial neural networks:

    • Knowledge acquisition
    • Skill refinement[2014]

24. What is a Hopfield network? Explain how this network operates and achieves its desirable features.

    [2018, 2014]

25. What is reinforcement learning? State and explain the steps of Rosenblatt’s perceptron learning algorithm.

    [2019]

26. Mention the different architectures of artificial neural networks.

    [2019]

27. What does the hidden layer hide? Why is a single perceptron unable to learn XOR function?

    [2019]

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