MCQOPTIONS
Saved Bookmarks
MCQOPTIONS
This section includes 15 Mcqs, each offering curated multiple-choice questions to sharpen your Neural Networks knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
What was the goal of shunting activation model? |
| A. | to make system dynamic |
| B. | to keep operating range of activation value to a specified range |
| C. | to make system static |
| D. | can be either for dynamic or static, depending on inputs |
| Answer» C. to make system static | |
| 2. |
Who proposed the shunting activation model? |
| A. | rosenblatt |
| B. | hopfield |
| C. | perkel |
| D. | grossberg |
| Answer» E. | |
| 3. |
Which models belongs to main subcategory of activation models?a) additive & subtractive activation modelsb) additive & shunting activation modelsc) subtractive & shunting activation modelsd) all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model? |
| A. | additive & subtractive activation modelsb) additive & shunting activation modelsc) subtractive & shunting activation modelsd) all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model?a) f(x)=x |
| B. | additive & shunting activation modelsc) subtractive & shunting activation modelsd) all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model?a) f(x)=xb) f(x)=x2 |
| C. | subtractive & shunting activation modelsd) all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model?a) f(x)=xb) f(x)=x2c) f(x)=x3 |
| D. | all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model?a) f(x)=xb) f(x)=x2c) f(x)=x3d) none of the mentionedView Answer |
| Answer» C. subtractive & shunting activation modelsd) all of the mentioned 9.What is the assumption of perkels model, if f(x) is the output function in additive activation model?a) f(x)=xb) f(x)=x2c) f(x)=x3 | |
| 4. |
What’s the actual reason behind the boundedness of the output function in activation dynamics? |
| A. | limited neural fluid |
| B. | limited fan in capacity of inputs |
| C. | both limited neural fluid & fan in capacity |
| D. | none of the mentioned |
| Answer» E. | |
| 5. |
WHO_PROPOSED_THE_SHUNTING_ACTIVATION_MODEL??$ |
| A. | rosenblatt |
| B. | hopfield |
| C. | perkel |
| D. | grossberg |
| Answer» E. | |
| 6. |
WHAT_IS_THE_ASSUMPTION_OF_PERKELS_MODEL,_IF_F(X)_IS_THE_OUTPUT_FUNCTION_IN_ADDITIVE_ACTIVATION_MODEL??$ |
| A. | f(x)=x |
| B. | f(x)=x<sup>2</sup> |
| C. | f(x)=x<sup>3</sup> |
| D. | none of the mentioned |
| Answer» B. f(x)=x<sup>2</sup> | |
| 7. |
What was the goal of shunting activation model?$ |
| A. | to make system dynamic |
| B. | to keep operating range of activation value to a specified range |
| C. | to make system static |
| D. | can be either for dynamic or static, depending on inputs |
| Answer» C. to make system static | |
| 8. |
Which models belongs to main subcategory of activation models? |
| A. | additive & subtractive activation models |
| B. | additive & shunting activation models |
| C. | subtractive & shunting activation models |
| D. | all of the mentioned |
| Answer» C. subtractive & shunting activation models | |
| 9. |
What is global stability? |
| A. | when both synaptic & activation dynamics are simultaneously used & are in equilibrium |
| B. | when only synaptic & activation dynamics are used |
| C. | when only synaptic dynamics in equilibrium |
| D. | none of the mentioned |
| Answer» B. when only synaptic & activation dynamics are used | |
| 10. |
What is structural stability? |
| A. | when both synaptic & activation dynamics are simultaneously used & are in equilibrium |
| B. | when only synaptic dynamics in equilibrium |
| C. | when only synaptic dynamics in equilibrium |
| D. | none of the mentioned |
| Answer» E. | |
| 11. |
Broadly how many kinds of stability can be defined in neural networks? |
| A. | 1 |
| B. | 3 |
| C. | 2 |
| D. | 4 |
| Answer» D. 4 | |
| 12. |
What is noise saturation dilemma? |
| A. | at saturation state neuron will stop working, while biologically it’s not feasible |
| B. | how can a neuron with limited operating range be made sensitive to nearly unlimited range of inputs |
| C. | can be either way |
| D. | none of the mentioned |
| Answer» C. can be either way | |
| 13. |
What’s the actual reason behind the boundedness of the output function in activation dynamics?$ |
| A. | limited neural fluid |
| B. | limited fan in capacity of inputs |
| C. | both limited neural fluid & fan in capacity |
| D. | none of the mentioned |
| Answer» E. | |
| 14. |
In activation dynamics is output function bounded? |
| A. | yes |
| B. | no |
| Answer» B. no | |
| 15. |
Activation value is associated with? |
| A. | potential at synapses |
| B. | cell membrane potential |
| C. | all of the mentioned |
| D. | none of the mentioned |
| Answer» C. all of the mentioned | |