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Objective Type Set
Online MCQ Assignment
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1. For what purpose Feedback neural networks are primarily used?
a) classification
b) feature mapping
c) pattern mapping
d) none of the mentioned

Answer: d [Reason:] Feedback neural networks are primarily used for pattern storage.

2. Presence of false minima will have what effect on probability of error in recall?
a) directly
b) inversely
c) no effect
d) directly or inversely

Answer: a [Reason:] Presence of false minima will increase the probability of error in recall.

3. How is effect false minima reduced
a) deterministic update of weights
b) stochastic update of weights
c) deterministic or stochastic update of weights
d) none of the mentioned

Answer: b [Reason:] Presence of false minima can be reduced by stochastic update.

4. Is Boltzman law practical for implementation?
a) yes
b) no

Answer: b [Reason:] Boltzman law is too slow for implementation.

5. For practical implementation what type of approximation is used on boltzman law?
a) max field approximation
b) min field approximation
c) hopfield approximation
d) none of the mentioned

Answer: d [Reason:] For practical implementation mean field approximation is used.

6. What happens when we use mean field approximation with boltzman learning?
a) it slows down
b) it get speeded up
c) nothing happens
d) may speedup or speed down

Answer: b [Reason:] Boltzman learning get speeded up using mean field approximation.

7. Approximately how much times the boltzman learning get speeded up using mean field approximation?
a) 5-10
b) 10-30
c) 30-50
d) 50-70

Answer: b [Reason:] Boltzman learning get speeded up 10-30 using mean field approximation.

8.False minima can be reduced by deterministic updates?
a) yes
b) no

Answer: b [Reason:] Presence of false minima can be reduced by stochastic update.

9. In boltzman learning which algorithm can be used to arrive at equilibrium?
a) hopfield
b) mean field
c) hebb
d) none of the mentioned

Answer: d [Reason:] Metropolis algorithm can be used to arrive at equilibrium.

10. Boltzman learning is a?
a) fast process