Neural Network

Applications of Neural Networks

Question 1
Marks : +2 | -2
Pass Ratio : 100%
Which is the most direct application of neural networks?
vector quantization
pattern mapping
pattern classification
control applications
Explanation:
Its is the most direct and multilayer feedforward networks became popular because of this.
Question 2
Marks : +2 | -2
Pass Ratio : 100%
Which application out of these of robots can be made of single layer feedforward network?
wall climbing
rotating arm and legs
gesture control
wall following
Explanation:
Wall folloing is a simple task and doesn’t require any feedback.
Question 3
Marks : +2 | -2
Pass Ratio : 100%
Neuro – Fuzzy systems can lead to more powerful neural network?
yes
no
may be
cannot be determined
Explanation:
If fuzzy logic is incorporated into conventional ANN models, more powerful systems can be created.
Question 4
Marks : +2 | -2
Pass Ratio : 100%
which of the following is false?
neural networks are artificial copy of the human brain
neural networks have high computational rates than conventional computers
neural networks learn by examples
none of the mentioned
Explanation:
All statements are true for a neural network.
Question 5
Marks : +2 | -2
Pass Ratio : 100%
What happens in upper subnet of the hamming network?
classification
storage
output
none of the mentioned
Explanation:
In upper subnet, competitive interaction among units take place.
Question 6
Marks : +2 | -2
Pass Ratio : 100%
The competition in upper subnet of hamming network continues till?
only one unit remains negative
all units are destroyed
output of only one unit remains positive
none of the mentioned
Explanation:
The competition in upper subnet of hamming network continues till output of only one unit remains positive.
Question 7
Marks : +2 | -2
Pass Ratio : 100%
what is true about single layer associative neural networks?
performs pattern recognition
can find the parity of a picture
can determine whether two or more shapes in a picture are connected or not
none of the mentioned
Explanation:
It can only perform pattern recognition, rest is not true for a single layer neural.
Question 8
Marks : +2 | -2
Pass Ratio : 100%
What does the matching score at first layer in recognition hamming network is indicative of?
dissimilarity of input pattern with patterns stored
noise immunity
similarity of input pattern with patterns stored
none of the mentioned
Explanation:
Matching score is simply a indicative of similarity of input pattern with patterns stored.
Question 9
Marks : +2 | -2
Pass Ratio : 100%
For what purpose, hamming network is suitable?
classification
association
pattern storage
none of the mentioned
Explanation:
Hamming network performs template matching between stored templates and inputs.
Question 10
Marks : +2 | -2
Pass Ratio : 100%
What are pros of neural networks over computers?
they have ability to learn b examples
they have real time high computational rates
they have more tolerance
all of the mentioned
Explanation:
Because of their parallel structure, they have high computational rates than conventional computers, so all are true.