Neural Network Questions and Answers – ART

This set of Neural Networks Multiple Choice Questions & Answers (MCQs) focuses on “ART″.

1. An auto – associative network is?
a) network in neural which contains feedback
b) network in neural which contains loops
c) network in neural which no loops
d) none of the mentioned
View Answer

Answer: a
Explanation: An auto – associative network contains feedback.

2. What is true about sigmoidal neurons?
a) can accept any vectors of real numbers as input
b) outputs a real number between 0 and 1
c) they are the most common type of neurons
d) all of the mentioned
View Answer

Answer: d
Explanation: These all statements itself defines sigmoidal neurons.

3. The bidirectional associative memory is similar in principle to?
a) hebb learning model
b) boltzman model
c) Papert model
d) none of the mentioned
View Answer

Answer: d
Explanation: The bidirectional associative memory is similar in principle to Hopfield model.
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4. What does ART stand for?
a) Automatic resonance theory
b) Artificial resonance theory
c) Adaptive resonance theory
d) None of the mentioned
View Answer

Answer: c
Explanation: ART stand for Adaptive resonance theory.

5. What is the purpose of ART?
a) take care of approximation in a network
b) take care of update of weights
c) take care of pattern storage
d) none of the mentioned
View Answer

Answer: d
Explanation: Adaptive resonance theory take care of stability plasticity dilemma.
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6. hat type learning is involved in ART?
a) supervised
b) unsupervised
c) supervised and unsupervised
d) none of the mentioned
View Answer

Answer: b
Explanation: CPN is a unsupervised learning.

7. What type of inputs does ART – 1 receives?
a) bipolar
b) binary
c) both bipolar and binary
d) none of the mentiobned
View Answer

Answer: b
Explanation: ART – 1 receives only binary inputs.
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8. A greater value of ‘p’ the vigilance parameter leads to?
a) small clusters
b) bigger clusters
c) no change
d) none of the mentioned
View Answer

Answer: a
Explanation: Input samples associated with same neuron get reduced.

9. ART is made to tackle?
a) stability problem
b) hard problems
c) storage problems
d) none of the mentioned
View Answer

Answer: d
Explanation: ART is made to tackle stability – plasticity dilemma.
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10. What does vigilance parameter in ART determines?
a) number of possible outputs
b) number of desired outputs
c) number of acceptable inputs
d) none of the mentioned
View Answer

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

Sanfoundry Global Education & Learning Series – Neural Networks.

To practice all areas of Neural Networks, here is complete set on 1000+ Multiple Choice Questions and Answers.

If you find a mistake in question / option / answer, kindly take a screenshot and email to [email protected]

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Manish Bhojasia - Founder & CTO at Sanfoundry
Manish Bhojasia, a technology veteran with 20+ years @ Cisco & Wipro, is Founder and CTO at Sanfoundry. He lives in Bangalore, and focuses on development of Linux Kernel, SAN Technologies, Advanced C, Data Structures & Alogrithms. Stay connected with him at LinkedIn.

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