Q.1
For what purpose Feedback neural networks are primarily used?
  • a) classification
  • b) feature mapping
  • c) pattern mapping
  • d) none of the mentioned
Q.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
Q.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
Q.4
Is Boltzman law practical for implementation?
  • a) yes
  • b) no
Q.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
Q.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
Q.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
Q.8
False minima can be reduced by deterministic updates?
  • a) yes
  • b) no
Q.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
Q.10
Boltzman learning is a?
  • a) fast process
  • b) steady process
  • c) slow process
  • d) none of the mentioned
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