Neural Network

Multi Layer Feedforward Neural Network

Question 1
Marks : +2 | -2
Pass Ratio : 100%
Th CPN provides practical approach for implementing?
patter approximation
pattern classification
pattern mapping
pattern clustering
Explanation:
CPN i.e counterpropagation network provides a practical approach for implementing pattern mapping.
Question 2
Marks : +2 | -2
Pass Ratio : 100%
What consist of a basic counterpropagation network?
a feedforward network only
a feedforward network with hidden layer
two feedforward network with hidden layer
none of the mentioned
Explanation:
Counterpropagation network consist of two feedforward network with a common hidden layer.
Question 3
Marks : +2 | -2
Pass Ratio : 100%
In which type of networks training is completely avoided?
GRNN
PNN
GRNN and PNN
None of the mentioned
Explanation:
In GRNN and PNN networks training is completely avoided.
Question 4
Marks : +2 | -2
Pass Ratio : 100%
Pattern recall takes more time for?
MLFNN
Basis function
Equal for both MLFNN and basis function
None of the mentioned
Explanation:
The first layer of basis function involves computations.
Question 5
Marks : +2 | -2
Pass Ratio : 100%
How does the name counterpropagation signifies its architecture?
its ability to learn inverse mapping functions
its ability to learn forward mapping functions
its ability to learn forward and inverse mapping functions
none of the mentioned
Explanation:
Counterpropagation network has ability to learn forward and inverse mapping functions.
Question 6
Marks : +2 | -2
Pass Ratio : 100%
What is the advantage of basis function over mutilayer feedforward neural networks?
training of basis function is faster than MLFFNN
training of basis function is slower than MLFFNN
storing in basis function is faster than MLFFNN
none of the mentioned
Explanation:
The main advantage of basis function is that the training of basis function is faster than MLFFNN.
Question 7
Marks : +2 | -2
Pass Ratio : 100%
Why is the training of basis function is faster than MLFFNN?
because they are developed specifically for pattern approximation
because they are developed specifically for pattern classification
because they are developed specifically for pattern approximation or classification
none of the mentioned
Explanation:
Training of basis function is faster than MLFFNN because they are developed specifically for pattern approximation or classification.
Question 8
Marks : +2 | -2
Pass Ratio : 100%
What does PNN do?
function approximation task
pattern classification task
function approximation and pattern classification task
none of the mentioned
Explanation:
PNN stand for Probabilistic Neural Networks.
Question 9
Marks : +2 | -2
Pass Ratio : 100%
What is the use of MLFFNN?
to realize structure of MLP
to solve pattern classification problem
to solve pattern mapping problem
to realize an approximation to a MLP
Explanation:
MLFFNN stands for multilayer feedforward network and MLP stands for multilayer perceptron.
Question 10
Marks : +2 | -2
Pass Ratio : 100%
What does GRNN do?
function approximation task
pattern classification task
function approximation and pattern classification task
none of the mentioned
Explanation:
GRNN stand for Generalized Regression Neural Networks.