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Objective Type Set
Online MCQ Assignment
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1. An instar can respond to a set of input vectors even if its not trained to capture the behaviour of the set?
a) yes
b) no

Answer: a [Reason:] An instar can respond to a set of input vectors even if it is trained to capture the average behaviour of the set.

2. The weight change in plain hebbian learning is?
a) 0
b) 1
c) 0 or 1
d) none of the mentioned

Answer: d [Reason:] The weight change in plain hebbian learning can never be zero.

3. What is the nature of weights in plain hebbian learning?
a) convergent
b) divergent
c) may be convergent or divergent
d) none of the mentioned

Answer: b [Reason:] In plain hebbian learning weights keep growing without bound.

4. How can divergence be prevented?
a) using hopfield criteria
b) sangers rule
c) ojas rule
d) sangers or ojas rule

Answer: d [Reason:] Divergence can be prevented by using sangers or ojas rule.

5. By normalizing the weight at every stage can we prevent divergence?
a) yes
b) no

Answer: a [Reason:] ||w|| = 1 .

6. What is ojas rule?
a) finds a unit weight vector
b) maximises the mean squared output
c) minimises the mean squared output
d) none of the mentioned

Answer: d [Reason:] Ojas rule finds a unit weight vector and maximises the mean squared output.

7. What is the other name of feedback layer in competitive neural networks?
a) feedback layer
b) feed layer
c) competitive layer
d) no such name exist

Answer: c [Reason:] Feedback layer in competitive neural networks is also known as competitive layer.

8. what kind of feedbacks are given in competitive layer?
a) self excitatory to self and others
b) inhibitory to self and others
c) self excitatory to self and inhibitory to others
d) inhibitory to self and excitatory to others

Answer: c [Reason:] The second layer of competitive networks have self excitatory to self and inhibitory to others feedbacks to make it competitive.

9. Generally how many kinds of pattern storage network exist?
a) 2
b) 3
c) 4
d) 5

Answer: b [Reason:] Namely, temporary storage, Short term memory, Long term memory.

10. In competitive learning, node with highest activation is the winner, is it true?
a) yes
b) no