Wayground logo

Free Printable Worksheets

Font size

S
M
L
XL
Worksheets

Cognitions 2.0#7

Total questions: 20

Worksheet time: 10mins

Name
Class
Date
1.

Which of the following neural networks uses supervised learning?

a. Multilayer perceptron

b. Self-organizing feature map

c. Hopfield network

a)

a only

b)

b only

c)

a and c only

d)

a and b only

2.

A 3-input neuron is trained to output a zero when the input is 110 and a one when the input is 111. After generalisation, the output will be zero when and only when the input is:

a)

000 or 110 or 011 or 101

b)

010 or 100 or 110 or 101

c)

000 or 010 or 110 or 100

d)

100 or 110 or 001 or 101

3.

A 4-input neuron has weights 1, 2, 3 and 4. The transfer function is linear with the constant of proportionality being equal to 2. The inputs are 4, 10, 5 and 20 respectively. The output will be:

a)

238

b)

76

c)

119

d)

101

4.

Which of the following is true?

Single layer associative neural networks do not have the ability to:

(i) perform pattern recognition

(ii) find the parity of a picture

(iii)determine whether two or more shapes in a picture are connected or not

a)

Only(ii) and (iii) are true

b)

Only(ii) is true

c)

(i), (ii) and (iii) are true

d)

Only (i) is true

5.

Which of the following is true?

(i) On average, neural networks have higher computational rates than conventional computers.

(ii) Neural networks learn by example.

(iii) Neural networks mimic the way the human brain works.

a)

(i), (ii) and (iii) are true

b)

(ii) and (iii) are true, (i) is false

c)

(i) and (iii) are true , (ii) is false

d)

(i), (ii) and (iii) are false

6.

Which of the following is true for neural networks?

(i) The training time depends on the size of the network.

(ii) Neural networks can be simulated on a conventional computer.

(iii)Artificial neurons are identical in operation to biological ones.

a)

all of them are true.

b)

(ii) is true.

c)

 (i) and (ii) are true.

d)

(i) is true

7.

Which of the following is not an example of an unsupervised neural network?

a)

Self-organising feature map

b)

Hebb network

c)

Both 1 and 2

d)

Back Propagation network

8.

Which boolean operation on two variables can be represented by a single perceptron layer?

A) X1 AND X2

B) X1 OR X2

C) X1 NOR X2

D) X1 XOR X2

a)

D only

b)

C and D only

c)

A,B and C only

d)

A,B,C and D only

9.

What does RNN stand for?

a)

Recurring Neural

b)

NetworkRemovable Neural Network

c)

Recurrent Neural Network

d)

None

10.

Given below are two statements:

If two variables V1 and V2 are used for clustering, then consider the following statements for k means clustering with k = 3:

Statement I: If V1 and V2 have a correlation of 1 the cluster centroid will be in a straight line.

Statement II: If V1 and V2 have a correlation of 0 the cluster centroid will be in a straight line.

In light of the above statements. choose the correct answer from the options given below

a)

Both Statement I and Statement II are true

b)

Both Statement I and Statement II are false

c)

Statement I is correct but Statement II is false

d)

Statement I is incorrect but Statement II is true

11.

In neural network, the network capacity is defined as

a)

The traffic carry capacity of the network

b)

The total number of nodes in the network

c)

The number of patterns that can be stored and recalled in a network

d)

None of the above

12.

What is the auto association task in a neural network?

a)

input pattern keeps on changing

b)

output pattern keeps on changing

c)

input pattern has become static

d)

None

13.

What is the objective of linear auto-associative feedforward networks?

a)

to associate a given pattern with itself

b)

to associate a given pattern with others

c)

to associate output with input

d)

None of the mentioned

14.

How are input layer units connected to the second layer in competitive learning networks?

a)

feedforward manner

b)

feedback manner

c)

feedforward and feedback

d)

feedforward or feedback

15.

What are models in Neural Networks?

a)

representation of biological neural networks

b)

mathematical representation of our understanding

c)

both first and second

d)

none of the above

16.

What is Plasticity in Neural networks?

a)

input pattern has become static

b)

input pattern keeps on changing

c)

output pattern keeps on changing

d)

none of the above

17.

Artificial Neural Network is based on which approach?

a)

Weak Artificial Intelligence approach

b)

Cognitive Artificial Intelligence approach

c)

Strong Artificial Intelligence approach

d)

Applied Artificial Intelligence approach

18.

Which one of the following is a blind search?

a)

Depth-search first

b)

Best-first-search

c)

Depth-first-search

d)

Best-search-first

19.

Among the following which type of neural network architectures are used for pattern recognition?

a)

Kohonen SOM

b)

Radial Basis Function Network

c)

Multilayer Perception

d)

All of the above

20.

What is hebb’s rule of learning?

a)

 the system learns from its past mistakes

b)

 the system recalls previous reference inputs & respective ideal

outputs

c)

 the strength of neural connection get modified accordingly

d)

none of the above