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1. What is ART in neural networks?
a) automatic resonance theory
b) artificial resonance theory
c) adaptive resonance theory
d) none of the mentioned

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Answer: c [Reason:] It is full form of ART & is basic q&a.

2. What is an activation value?
a) weighted sum of inputs
b) threshold value
c) main input to neuron
d) none of the mentioned

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Answer: a [Reason:] It is definition of activation value & is basic q&a.

3. Positive sign of weight indicates?
a) excitatory input
b) inhibitory input
c) can be either excitatory or inhibitory as such
d) none of the mentioned

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Answer: a [Reason:] Sign convention of neuron.

4. Negative sign of weight indicates?
a) excitatory input
b) inhibitory input
c) excitatory output
d) inhibitory output

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Answer: b [Reason:] Sign convention of neuron.

5. The amount of output of one unit received by another unit depends on what?
a) output unit
b) input unit
c) activation value
d) weight

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Answer: d [Reason:] Activation is sum of wieghted sum of inputs, which gives desired output..hence output depends on weights.

6. The process of adjusting the weight is known as?
a) activation
b) synchronisation
c) learning
d) none of the mentioned

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Answer: c [Reason:] Basic definition of learning in neural nets .

7. The procedure to incrementally update each of weights in neural is referred to as?
a) synchronisation
b) learning law
c) learning algorithm
d) both learning algorithm & law

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Answer: d [Reason:] Basic definition of learning law in neural.

8. In what ways can output be determined from activation value?
a) deterministically
b) stochastically
c) both deterministically & stochastically
d) none of the mentioned

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Answer: c [Reason:] This is the most important trait of input processing & output determination in neural networks.

9. How can output be updated in neural network?
a) synchronously
b) asynchronously
c) both synchronously & asynchronously
d) none of the mentioned

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Answer: c [Reason:] Output can be updated at same time or at different time in the networks.

10. What is asynchronous update in neural netwks?
a) output units are updated sequentially
b) output units are updated in parallel fashion
c) can be either sequentially or in parallel fashion
d) none of the mentioned

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Answer: a [Reason:] Output are updated at different time in the networks.

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