JNTU III B.Tech II Semester Supplimentary Examinations, Aug/Sep 2008
(Computer Science & Engineering)
1. (a) Explain how to build invariances into neural network design.
(b) Explain how to build prior information into neural network design.
2. (a) Write in detail about error-detection learning.
(b) Write in detail about memory brief learning.
3. Explain the following briefly:
(a) Steepest descent method
(b) Newton’s method
(c) Gauss-Newton?s method
(d) Convergence of LMS algorithm.
4. Explain in detail about the following methods which are useful in improving back
(a) Maximizing information content
(b) Activation function.
5. (a) Write and explain the Back propagation algorithm.
(b) Write about applications of Back propagation network.
6. What are the self organizing maps? Explain the architecture and the training
algorithm used for Kohonen’s SOMs.
7. Explain the mathematical model for describing the dynamics of a nonlinear system.
8. (a) What is the relationship between the number of neurons and number of system
states in a typical Hopfield network.
(b) Write down the steps involved in the retrieval phase of operation of a hopfiled network and explain each step in detail.