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Neural Networks Multiple Choice Questions on “Dynamics″.
1. Weight state i.e set of weight values are determined by what kind of dynamics?
A. synaptic dynamics
B. neural level dynamics
C. can be either synaptic or neural dynamics
D. none of the mentioned
Answer: A
Clarification: Weights are best determined by synaptic dynamics, as it is one fastest & precise dynamics occurring.
2. Which is faster neural level dynamics or synaptic dynamics?
A. neural level
B. synaptic
C. both equal
D. insufficient information
Answer: A
Clarification: Since neural level dyna,ics depends on input fluctuations & these take place at every milliseconds.
3. During activation dynamics does weight changes?
A. yes
B. no
Answer: B
Clarification: During activation dynamics, synaptic weights don’t change significantly & hence assumed to be constant.
4. Activation dynamics is referred as?
A. short term memory
B. long term memory
C. either short or long term
D. both short & long term
Answer: a
Clarification: It depends on input pattern, & input changes from moment to moment, hence Short term memory.
5. Synaptic dynamics is referred as?
A. short term memory
B. long term memory
C. either short or long term
D. both short & long term
Answer: B
Clarification: Synaptic dynamics don’t change for a given set of training inputs, hence long term memory.
6. What is classification?
A. deciding what features to use in a pattern recognition problem
B. deciding what class an input pattern belongs to
C. deciding what type of neural network to use
D. none of the mentioned
Answer: B
Clarification: Follows from basic definition of classification.
7. What is generalization?
A. the ability of a pattern recognition system to approximate the desired output values for pattern vectors which are not in the test set.
B. the ability of a pattern recognition system to approximate the desired output values for pattern vectors which are not in the training set.
C. can be either way
D. none of the mentioned
Answer: B
Clarification: Follows from basic definition of generalization.
8. What are models in neural networks?
A. mathematical representation of our understanding
B. representation of biological neural networks
C. both way
D. none of the mentioned
Answer: C
Clarification: Model should be close to our biological neural systems, so that we can have high efficiency in machines too.
9. What kind of dynamics leads to learning laws?
A. synaptic
B. neural
C. activation
D. both synaptic & neural
Answer: A
Clarification: Since weights are dependent on synaptic dynamics, hence learning laws.
10. Changing inputs affects what kind of dynamics directly?
A. synaptic
B. neural
C. activation
D. both synaptic & neural
Answer: C
Clarification: Activation dynamics depends on input pattern, hence any change in input pattern will affect activation dynamics of neural networks.