250+ MCQs on Stability & Convergence and Answers

Neural Networks Multiple Choice Questions on “Convergence & stability″.

1. Stability refers to adjustment in behaviour of weights during learning?
A. yes
B. no
Answer: B
Clarification: Stability refers to equilibrium behaviour of activation state.

2. Convergence refers to equilibrium behaviour of activation state?
A. yes
B. no
Answer: B
Clarification: Convergence refers to adjustment in behaviour of weights during learning.

3. 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
Clarification: Convergence is responsible for minimization of error between the desired & actual outputs.

4. Stability is minimization of error between the desired & actual outputs?
A. yes
B. no
Answer: B
Clarification: Convergence is minimization of error between the desired & actual outputs.

5. How many trajectories may terminate at same equilibrium state?
A. 1
C. 2
C. many
D. none
Answer: C
Clarification: There may be several trajectories that may settle to same equilibrium state.

6. If weights are not symmetric i.e cik =! cki, then what happens?
A. network may exhibit periodic oscillations of states
B. no oscillations as it doesn’t depend on it
C. system is stable
D. system in practical equilibrium
Answer: A
Clarification: At this situation system exhibits some unwanted oscillations.

7. Is pattern storage possible if system has chaotic stability?
A. yes
B. no
Answer: A
Clarification: Pattern storage is possible if any network exhibits either fixed point, oscillatory, chaotic stability.

8. If states of system experience basins of attraction, then system may achieve what kind of stability?
A. fixed point stability
B. oscillatory stability
C. chaotic stability
D. none of the mentioned
Answer: C
Clarification: Basins of attraction is a property of chaotic stability.

9. What is an objective of a learning law?
A. to capture pattern information in training set data
B. to modify weights so as to achieve output close to desired output
C. it should lead to convergence of system or its weights
D. all of the mentioned
Answer: d
Clarification: These all are some objectives of learning laws.

10. A network will be useful only if, it leads to equilibrium state at which there is no change of state?
A. yes
B. no
Answer: A
Clarification: Its the basic condition for stability.