Neural Network Questions and Answers – Analysis of Pattern Storage Networks – 1

This set of Neural Networks Multiple Choice Questions & Answers (MCQs) focuses on “Analysis Of Pattern Storage Networks – 1″.

1. For what purpose energy minima are used?
a) pattern classification
b) patten mapping
c) pattern storage
d) none of the mentioned
View Answer

Answer: c
Explanation: Energy minima are used for pattern storage.

2. Is it possible to determine exact number of basins of attraction in energy landscape?
a) yes
b) no
View Answer

Answer: b
Explanation: It is not possible to determine exact number of basins of attraction in energy landscape.

3. What is capacity of a network?
a) number of inputs it can take
b) number of output it can deliver
c) number of patterns that can be stored
d) none of the mentioned
View Answer

Answer: c
Explanation: The capacity of a network is the number of patterns that can be stored.
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4. Can probability of error in recall be reduced?
a) yes
b) no
View Answer

Answer: a
Explanation: Probability of error in recall be reduced by adjusting weights in such a way that it is matched to probability distribution of desired patterns.

5. Number of desired patterns is what of basins of attraction?
a) dependent
b) independent
c) dependent or independent
d) none of the mentioned
View Answer

Answer: b
Explanation: Number of desired patterns is independent of basins of attraction.

6. What happens when number of patterns is more than number of basins of attraction?
a) false wells
b) storage problem becomes hard problem
c) no storage and recall can take place
d) none of the mentioned
View Answer

Answer: b
Explanation: When number of patterns is more than number of basins of attraction then storage problem becomes hard problem.

7. What happens when number of patterns is less than number of basins of attraction?
a) false wells
b) storage problem becomes hard problem
c) no storage and recall can take place
d) none of the mentioned
View Answer

Answer: a
Explanation: False wells are created when number of patterns is less than number of basins of attraction.
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8. What is hopfield model?
a) fully connected feedback network
b) fully connected feedback network with symmetric weights
c) fully connected feedforward network
d) fully connected feedback network with symmetric weights
View Answer

Answer: b
Explanation: Hopfield model is fully connected feedback network with symmetric weights.

9. When are false wells created?
a) when number of patterns is more than number of basins of attraction
b) when number of patterns is less than number of basins of attraction
c) when number of patterns is same as number of basins of attraction
d) none of the mentioned
View Answer

Answer: b
Explanation: False wells are created when number of patterns is less than number of basins of attraction.
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10. When does storage problem becomes hard problem?
a) when number of patterns is more than number of basins of attraction
b) when number of patterns is less than number of basins of attraction
c) when number of patterns is same as number of basins of attraction
d) none of the mentioned
View Answer

Answer: a
Explanation: When number of patterns is more than number of basins of attraction then storage problem becomes hard problem.

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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