Analysis of Pattern Storage MCQ

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• Why there is error in recall, when number of energy minima is more the required number of patterns to be stored?
  ক

  due to noise

  খ

  due to additional false maxima

  গ

  due to additional false minima

  ঘ

  none of the mentioned
• How hard problem can be solved?
  ক

  by providing additional units in a feedback network

  খ

  nothing can be done

  গ

  by removing units in hidden layer

  ঘ

  none of the mentioned
• What happens when number of available energy minima be more than number of patterns to be stored?
  ক

  no effect

  খ

  pattern storage is not possible in that case

  গ

  error in recall

  ঘ

  none of the mentioned
• What happens when number of available energy minima be less than number of patterns to be stored?
  ক

  pattern storage is not possible in that case

  খ

  pattern storage can be easily done

  গ

  pattern storage problem becomes hard problem for the network

  ঘ

  none of the mentioned
• The number of patterns that can be stored in a given network depends on?
  ক

  number of units

  খ

  strength of connecting links

  গ

  both number of units and strength of connecting links

  ঘ

  none of the mentioned
• When are stable states reached in energy landscapes, that can be used to store input patterns?
  ক

  mean of peaks and valleys

  খ

  maxima

  গ

  minima

  ঘ

  none of the mentioned
• What can be done by using non – linear output function for each processing unit in a feedback network?
  ক

  pattern classification

  খ

  recall

  গ

  pattern storage

  ঘ

  all of the mentioned
• Does linear autoassociative network have any practical use?
  ক

  yes

  খ

  no
• In a linear autoassociative network, if input is noisy than output will be noisy?
  ক

  yes

  খ

  no
• Which is a simplest pattern recognition task in a feedback network?
  ক

  heteroassociation

  খ

  autoassociation

  গ

  can be hetero or autoassociation, depends on situation

  ঘ

  none of the mentioned