What is the nature of weights in plain hebbian learning?

Neural Networks - Quiz(MCQ)

Divergent

Convergent

May be convergent or divergent

None of the Above

Correct Answer : Divergent

Explanation : In plain hebbian learning weights keep growing without bound.

Recently Updated in Neural Networks Questions

A greater value of 'p' the vigilance parameter leads to?

No change

Bigger clusters

Small clusters

None of the above

Correct Answer : Small clusters

Explanation : Input samples associated with same neuron get reduced.

What type of inputs does ART â€“ 1 receives?

binary

bipolar

both bipolar and binary

none of the above

Correct Answer : binary

Explanation : Adaptive resonance theory take care of stability plasticity dilemma.

What does vigilance parameter in ART determines?

Number of desired outputs

Number of possible outputs

Number of acceptable inputs

None of the above

Correct Answer : None of the above

Explanation : Vigilance parameter in ART determines the tolerance of matching process.

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