Neural Networks Questions and Answers - Stability & Convergence

1.Continuous perceptron learning is also known as delta learning?
a) yes
b) no

Answer: a
Explanation: Follows from basic definition of delta learning

2. Widrows LMS algorithm is also based on error correction learning?
a) yes
b) no

Answer: a
Explanation: It uses the instantaneous squared error between desired & actual output of unit

3. Error correction learning is type of?
a) supervised learning
b) unsupervised learning
c) can be supervised or unsupervised
d) none of the mentioned

Answer: a
Explanation: Since desired output for an input is known

4. Error correction learning is like learning with teacher?
a) yes
b) no

Answer: a
Explanation: Since desired output for an input is known.

5. What is reinforcement learning?
a) learning is based on evaluative signal
b) learning is based o desired output for an input
c) learning is based on both desired output & evaluative signal
d) none of the mentioned

Answer: a
Explanation: Reinforcement learning is based on evaluative signal.

6. Stability refers to adjustment in behaviour of weights during learning?
a) yes
b) no

Answer: b
Explanation: Stability refers to equilibrium behaviour of activation state

7. Convergence refers to equilibrium behaviour of activation state?
a) yes
b) no

Answer: b
Explanation:Convergence refers to adjustment in behaviour of weights during learning

8. What leads to minimization of error between the desired & actual outputs?
a) stability
b) convergence
c) either stability or convergence
d) none of the mentioned

Answer: b
Explanation:Convergence is responsible for minimization of error between the desired & actual outputs

9. Stability is minimization of error between the desired & actual outputs?
a) yes
b) no

Answer: b
Explanation: Convergence is minimization of error between the desired & actual outputs.

10. How many trajectories may terminate at same equilibrium state?
a) 1
b) 2
c) many
d) none

Answer: c
Explanation: There may be several trajectories that may settle to same equilibrium state.