Explore topic-wise MCQs in Neural Networks.

This section includes 12 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.

How does the name counterpropagation signifies its architecture?

A. its ability to learn inverse mapping functions
B. its ability to learn forward mapping functions
C. its ability to learn forward and inverse mapping functions
D. none of the mentioned
Answer» D. none of the mentioned
2.

What consist of a basic counterpropagation network?

A. a feedforward network only
B. a feedforward network with hidden layer
C. two feedforward network with hidden layer
D. none of the mentioned
Answer» D. none of the mentioned
3.

WHAT_CONSIST_OF_A_BASIC_COUNTERPROPAGATION_NETWORK??$

A. a feedforward network only
B. a feedforward network with hidden layer
C. two feedforward network with hidden layer
D. none of the mentioned
Answer» D. none of the mentioned
4.

How_does_the_name_counterpropagation_signifies_its_architecture?$

A. its ability to learn inverse mapping functions
B. its ability to learn forward mapping functions
C. its ability to learn forward and inverse mapping functions
D. none of the mentioned
Answer» D. none of the mentioned
5.

Th CPN provides practical approach for implementing?

A. patter approximation
B. pattern classification
C. pattern mapping
D. pattern clustering
Answer» D. pattern clustering
6.

What does PNN do?

A. function approximation task
B. pattern classification task
C. function approximation and pattern classification task
D. none of the mentioned
Answer» C. function approximation and pattern classification task
7.

What does GRNN do?

A. function approximation task
B. pattern classification task
C. function approximation and pattern classification task
D. none of the mentioned
Answer» B. pattern classification task
8.

In which type of networks training is completely avoided?

A. GRNN
B. PNN
C. GRNN and PNN
D. None of the mentioned
Answer» D. None of the mentioned
9.

Pattern recall takes more time for?

A. MLFNN
B. Basis function
C. Equal for both MLFNN and basis function
D. None of the mentioned
Answer» C. Equal for both MLFNN and basis function
10.

Why is the training of basis function is faster than MLFFNN?

A. because they are developed specifically for pattern approximation
B. because they are developed specifically for pattern classification
C. because they are developed specifically for pattern approximation or classification
D. none of the mentioned
Answer» D. none of the mentioned
11.

What is the advantage of basis function over mutilayer feedforward neural networks?

A. training of basis function is faster than MLFFNN
B. training of basis function is slower than MLFFNN
C. storing in basis function is faster than MLFFNN
D. none of the mentioned
Answer» B. training of basis function is slower than MLFFNN
12.

What is the use of MLFFNN?

A. to realize structure of MLP
B. to solve pattern classification problem
C. to solve pattern mapping problem
D. to realize an approximation to a MLP
Answer» E.