Neural Network Questions and Answers – Learning Basics – 1

This set of Neural Networks Aptitude Test focuses on “Learning Basics – 1”.

1. Activation models are?
a) dynamic
b) static
c) deterministic
d) none of the mentioned
View Answer

Answer: c
Explanation: Input/output patterns & the activation values may be considered as sample functions of random process.

2. If xb(t) represents differentiation of state x(t), then a stochastic model can be represented by?
a) xb(t)=deterministic model
b) xb(t)=deterministic model + noise component
c) xb(t)=deterministic model*noise component
d) none of the mentioned’
View Answer

Answer: b
Explanation: Noise is assumed to be additive in nature in stochastic models.

3. What is equilibrium in neural systems?
a) deviation in present state, when small perturbations occur
b) settlement of network, when small perturbations occur
c) change in state, when small perturbations occur
d) none of the mentioned
View Answer

Answer: b
Explanation: Follows from basic definition of equilibrium.
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4.What is the condition in Stochastic models, if xb(t) represents differentiation of state x(t)?
a) xb(t)=0
b) xb(t)=1
c) xb(t)=n(t), where n is noise component
d) xb(t)=n(t)+1
View Answer

Answer: c
Explanation: xb(t)=0 is condition for deterministic models, so option c is radical choice.

5. What is asynchronous update in a network?
a) update to all units is done at the same time
b) change in state of any one unit drive the whole network
c) change in state of any number of units drive the whole network
d) none of the mentioned
View Answer

Answer: b
Explanation: In asynchronous update, change in state of any one unit drive the whole network.
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6. Learning is a?
a) slow process
b) fast process
c) can be slow or fast in general
d) can’t say
View Answer

Answer: a
Explanation: Learning is a slow process.

7. What are the requirements of learning laws?
a) convergence of weights
b) learning time should be as small as possible
c) learning should use only local weights
d) all of the mentioned
View Answer

Answer: d
Explanation: These all are the some of basic requirements of learning laws.
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8. Memory decay affects what kind of memory?
a) short tem memory in general
b) older memory in general
c) can be short term or older
d) none of the mentioned
View Answer

Answer: a
Explanation: Memory decay affects short term memory rather than older memories.

9. What are the requirements of learning laws?
a) learning should be able to capture more & more patterns
b) learning should be able to grasp complex nonliear mappings
c) convergence of weights
d) all of the mentioned
View Answer

Answer: d
Explanation: These all are the some of basic requirements of learning laws.
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10. How is pattern information distributed?
a) it is distributed all across the weights
b) it is distributed in localised weights
c) it is distributed in certain proctive weights only
d) none of the mentioned
View Answer

Answer: a
Explanation: pattern information is highly distributed all across the weights.

Sanfoundry Global Education & Learning Series – Neural Networks.

To practice all areas of Neural Networks for aptitude tests, 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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