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Objective Type Questions & Answers


Neural Networks and Deep Learning-Unit-2 Objective Type Questions



1. For what purpose, hamming network is suitable?

A . classification

B . association

C . pattern storage

D . none of the mentioned

Answer



2. What does the activation value of winner unit is indicative of?

A . greater the degradation more is the activation value of winning units

B . greater the degradation less is the activation value of winning units

C . greater the degradation more is the activation value of other units

D . greater the degradation less is the activation value of other units

Answer



3.What does the matching score at first layer in recognition hamming network is indicative of?

A . dissimilarity of input pattern with patterns stored

B . noise immunity

C . similarity of input pattern with patterns stored

D . none of the mentioned

Answer



4. What is the objective of feature maps?

A . to capture the features in space of input patterns

B . to capture just the input patterns

C . update weights

D . to capture output patterns

Answer



5.How are weights updated in feature maps?

A . updated for winning unit only

B . updated for neighbours of winner only

C . updated for winning unit and its neighbours

D . none of the mentioned

Answer



6. In self organizing network, how is layer connected to output layer?

A . some are connected

B . all are one to one connected

C . each input unit is connected to each output unit

D . none of the mentioned

Answer



7. What is true for competitive learning?

A . nodes compete for inputs

B . process leads to most efficient neural representation of input space

C . typical for unsupervised learning

D . all of the mentioned

Answer



8. Use of nonlinear units in the feedback layer of competitive network leads to concept of?

A . feature mapping

B . pattern storage

C . pattern classification

D . pattern clustering

Answer



9. Kohonen self-organizing map referred to

A . The process of finding the right formal representation of a certain body of knowledge in order to represent it in a knowledge-based system

B . It automatically maps an external signal space into a system’s internal representational space. They are useful in the performance of classification tasks

C . A process where an individual learns how to carry out a certain task when making a transition from a situation in which the task cannot be carried out to a situation in which the same task under the same circumstances can be carried out.

D . None of these

Answer



10. Vector quantization is used for

A . Lossy data compression

B . Lossy data correction

C . Pattern recognition

D . All of the above

Answer



11. Vector quantization is used in

A . Video coding

B . Audio coding

C . Speech coding

D . All of the above

Answer



12. Characteristic of a vector quantizer

A . Multiple quantization indexes are represented by one codeword

B . Each input symbol is represented by a fixed-length codeword

C . Multiple input symbols are represented by one quantization index

D . All of the above

Answer





Relevant Materials :

Neural Networks and Deep Learning-Unit-1 Objective Type Questions - [ NNDL ]

Neural Networks and Deep Learning-Unit-2 Objective Type Questions - [ NNDL ]

Neural Networks and Deep Learning-Unit-3 Objective Type Questions - [ NNDL ]

Neural Networks and Deep Learning-Unit-4 Objective Type Questions - [ NNDL ]


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