JNTU III B.Tech II Semester Supplimentary Examinations, Aug/Sep 2008
(Computer Science & Engineering)
1. Draw and Explain in detail the block diagram of nervous system.
2. Explain concept of associate memory model using artificial neurons. With relevent
3. Explain the following:
(a) Gradient vector
(b) Hessian matrix.
4. The optimum number of hidden layers in back propagation is two. justify? What
happens if number of hidden layers increases? Explain.
5. (a) What are the steps involved in the back propagation algorithm. Explain
(b) What are the pattern recognition tasks that can perform by back propagation network.Explain Briefly
(c) What are the limitations of back propagation algorithm?
6. (a) Write about Kohenen model of self organized feature map.
(b) Write short notes on learning vector quantization.
7. (a) Discuss about stability and convergence in the context of an autonomous nonlinear dynamical system with equilibrium state.
(b) Draw and explain block diagram of related model.
8. What is gradient type Hopfield network? Differentiate between discrete time Hopfield network and gradient type Hopfield network.