# Neural Network Questions and Answers – Recall

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This set of Neural Networks Multiple Choice Questions & Answers (MCQs) focuses on “Recall″.

1. Lyapunov function is vector in nature?
a) yes
b) no

Explanation: Lyapunov function is scalar in nature.

2. What’s the role of lyaopunov fuction?
a) to determine stability
b) to determine convergence
c) both stability & convergence
d) none of the mentioned

Explanation: lyapunov is an energy function.

3. Did existence of lyapunov function is necessary for stability?
a) yes
b) no

Explanation: It is sufficient but not necessary condition.

4. V(x) is said to be lyapunov function if?
a) v(x) >=0
b) v(x) <=0
c) v(x) =0
d) none of the mentioned

Explanation: It is the condition for existence for lyapunov function.

5. What does cohen grossberg theorem?
a) shows the stability of fixed weight autoassociative networks
b) shows the stability of adaptive autoaassociative networks
c) shows the stability of adaptive heteroassociative networks
d) none of the mentioned

Explanation: Cohen grossberg theorem shows the stability of fixed weight autoassociative networks.

6. What does cohen grossberg kosko theorem?
a) shows the stability of fixed weight autoassociative networks
b) shows the stability of adaptive autoaassociative networks
c) shows the stability of adaptive heteroassociative networks
d) none of the mentioned

Explanation: Cohen grossberg kosko shows the stability of adaptive autoaassociative networks.

7. What does 3rd theorem that describe the stability of a set of nonlinear dynamical systems?
a) shows the stability of fixed weight autoassociative networks
b) shows the stability of adaptive autoaassociative networks
c) shows the stability of adaptive heteroassociative networks
d) none of the mentioned

Explanation: 3rd theorem of nonlinear dynamical systems, shows the stability of adaptive heteroassociative networks.

8. What happens during recall in neural networks?
a) weight changes are suppressed
b) input to the network determines the output activation
c) both process has to happen
d) none of the mentioned

Explanation: Follows from basic definition of Recall in a network.

9. Can a neural network learn & recall at the same time?
a) yes
b) no

Explanation: It was later proved by kosko in 1988.

10. In nearest neighbour case, the stored pattern closest to input pattern is recalled, where does it occurs?
a) feedback pattern classification
b) feedforward pattern classification
c) can be feedback or feedforward
d) none of the mentioned 