Explore topic-wise MCQs in Neural Networks.

This section includes 16 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks knowledge and support exam preparation. Choose a topic below to get started.

1.

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
Answer» E.
2.

ART is made to tackle?

A. stability problem
B. hard problems
C. storage problems
D. none of the mentioned
Answer» E.
3.

A greater value of ‘p’ the vigilance parameter leads to?

A. small clusters
B. bigger clusters
C. no change
D. none of the mentioned
Answer» B. bigger clusters
4.

What type of inputs does ART – 1 receives?

A. bipolar
B. binary
C. both bipolar and binary
D. none of the mentiobned
Answer» C. both bipolar and binary
5.

What does ART stand for?

A. Automatic resonance theory
B. Artificial resonance theory
C. Adaptive resonance theory
D. None of the mentioned
Answer» D. None of the mentioned
6.

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
Answer» B. network in neural which contains loops
7.

ART_IS_MADE_TO_TACKLE??$

A. stability problem
B. hard problems
C. storage problems
D. none of the mentioned
Answer» E.
8.

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
Answer» E.
9.

A greater value of ‘p’ the vigilance parameter leads to?#

A. small clusters
B. bigger clusters
C. no change
D. none of the mentioned
Answer» B. bigger clusters
10.

What type of inputs does ART – 1 receives?$

A. bipolar
B. binary
C. both bipolar and binary
D. none of the mentiobned
Answer» C. both bipolar and binary
11.

hat type learning is involved in ART?

A. supervised
B. unsupervised
C. supervised and unsupervised
D. none of the mentioned
Answer» C. supervised and unsupervised
12.

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
Answer» E.
13.

What is the full form of ART in Art?

A. Automatic resonance theory
B. Artificial resonance theory
C. Adaptive resonance theory
D. None of the mentioned
Answer» D. None of the mentioned
14.

The bidirectional associative memory is similar in principle to?

A. hebb learning model
B. boltzman model
C. Papert model
D. none of the mentioned
Answer» E.
15.

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
Answer» E.
16.

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
Answer» B. network in neural which contains loops