InterviewSolution
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InterviewSolution
This section includes InterviewSolutions, each offering curated multiple-choice questions to sharpen your knowledge and support exam preparation. Choose a topic below to get started.
| 1. |
In boltzman learning which algorithm can be used to arrive at equilibrium?(a) hopfield(b) mean field(c) hebb(d) none of the mentionedThe question was posed to me in an interview.The query is from Boltzman Machine topic in division Feedback Neural Networks of Neural Networks |
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Answer» The correct choice is (d) NONE of the mentioned |
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| 2. |
Boltzman learning is a?(a) fast process(b) steady process(c) slow process(d) none of the mentionedThis question was addressed to me in an international level competition.This intriguing question comes from Boltzman Machine topic in section Feedback Neural Networks of Neural Networks |
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Answer» RIGHT ANSWER is (d) NONE of the mentioned The explanation is: Explanation: Boltzman learning is a SLOW process. |
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| 3. |
False minima can be reduced by deterministic updates?(a) yes(b) noThis question was posed to me in my homework.My question is from Boltzman Machine topic in division Feedback Neural Networks of Neural Networks |
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Answer» Correct ANSWER is (B) no |
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| 4. |
Approximately how much times the boltzman learning get speeded up using mean field approximation?(a) 5-10(b) 10-30(c) 30-50(d) 50-70The question was posed to me in an internship interview.My query is from Boltzman Machine topic in section Feedback Neural Networks of Neural Networks |
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Answer» RIGHT choice is (b) 10-30 Explanation: Boltzman learning get speeded up 10-30using MEAN FIELD approximation. |
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| 5. |
For practical implementation what type of approximation is used on boltzman law?(a) max field approximation(b) min field approximation(c) hopfield approximation(d) none of the mentionedI got this question during an interview.My question comes from Boltzman Machine topic in division Feedback Neural Networks of Neural Networks |
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Answer» RIGHT ANSWER is (d) NONE of the mentioned To EXPLAIN: For practical implementation MEAN field approximation is used. |
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| 6. |
What happens when we use mean field approximation with boltzman learning?(a) it slows down(b) it get speeded up(c) nothing happens(d) may speedup or speed downI have been asked this question in an international level competition.My question is from Boltzman Machine in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct CHOICE is (b) it get speeded up |
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| 7. |
Is Boltzman law practical for implementation?(a) yes(b) noThe question was posed to me in a job interview.This question is from Boltzman Machine topic in section Feedback Neural Networks of Neural Networks |
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Answer» RIGHT option is (b) no The best EXPLANATION: Boltzman LAW is too SLOW for implementation. |
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| 8. |
How is effect false minima reduced(a) deterministic update of weights(b) stochastic update of weights(c) deterministic or stochastic update of weights(d) none of the mentionedThis question was posed to me in class test.My question is from Boltzman Machine topic in portion Feedback Neural Networks of Neural Networks |
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Answer» The correct answer is (B) stochastic UPDATE of weights |
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| 9. |
Presence of false minima will have what effect on probability of error in recall?(a) directly(b) inversely(c) no effect(d) directly or inverselyI got this question in final exam.The above asked question is from Boltzman Machine in portion Feedback Neural Networks of Neural Networks |
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Answer» The correct answer is (a) directly |
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| 10. |
For what purpose Feedback neural networks are primarily used?(a) classification(b) feature mapping(c) pattern mapping(d) none of the mentionedI had been asked this question in an internship interview.I'm obligated to ask this question of Boltzman Machine topic in section Feedback Neural Networks of Neural Networks |
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Answer» Right choice is (d) NONE of the mentioned |
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| 11. |
What may be the reasons for non zero probability of error in recalling?(a) spurious stable states(b) approximation in pattern environment representation(c) extra stable states(d) all of the mentionedThe question was posed to me during an interview.Question is taken from Boltzman Machine topic in section Feedback Neural Networks of Neural Networks |
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Answer» RIGHT answer is (d) all of the mentioned Explanation: These all are the primary reasons for EXISTENCE of NON zero probability of error. |
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| 12. |
Is exact representation of pattern environment possible?(a) yes(b) noI have been asked this question in an interview for internship.Enquiry is from Boltzman Machine in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct answer is (b) no |
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| 13. |
For which other task can boltzman machine be used?(a) pattern mapping(b) feature mapping(c) classification(d) pattern associationThe question was asked in my homework.The query is from Boltzman Machine in division Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT option is (d) PATTERN ASSOCIATION |
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| 14. |
How are energy minima related to probability of occurrence of corresponding patterns in the environment?(a) directly(b) inversely(c) directly or inversely(d) no relationThe question was posed to me by my college professor while I was bunking the class.The origin of the question is Boltzman Machine in section Feedback Neural Networks of Neural Networks |
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Answer» The correct option is (a) DIRECTLY |
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| 15. |
By using which method, boltzman machine reduces effect of additional stable states?(a) no such method exist(b) simulated annealing(c) hopfield reduction(d) none of the mentionedThe question was asked during a job interview.My enquiry is from Boltzman Machine in section Feedback Neural Networks of Neural Networks |
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Answer» Right choice is (b) simulated ANNEALING |
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| 16. |
What should be the aim of training procedure in boltzman machine of feedback networks?(a) to capture inputs(b) to feedback the captured outputs(c) to capture the behaviour of system(d) none of the mentionedThe question was asked by my school principal while I was bunking the class.This is a very interesting question from Boltzman Machine in section Feedback Neural Networks of Neural Networks |
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Answer» Right OPTION is (d) none of the mentioned |
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| 17. |
What consist of boltzman machine?(a) fully connected networkwith both hidden and visible units(b) asynchronous operation(c) stochastic update(d) all of the mentionedThis question was addressed to me in class test.My query is from Boltzman Machine in division Feedback Neural Networks of Neural Networks |
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Answer» Correct CHOICE is (d) all of the mentioned |
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| 18. |
Probability of error in recall of stored patterns can be reduced if?(a) patterns are stored appropriately(b) inputs are captured appropriately(c) weights are chosen appropriately(d) none of the mentionedThe question was posed to me in my homework.Question is taken from Boltzman Machine in division Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT option is (c) weights are chosen APPROPRIATELY |
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| 19. |
For what purpose is pattern environment useful?(a) determining structure(b) determining desired outputs(c) determining future inputs(d) none of the mentionedI have been asked this question in quiz.I'm obligated to ask this question of Boltzman Machine topic in division Feedback Neural Networks of Neural Networks |
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Answer» Right option is (d) none of the mentioned |
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| 20. |
What is pattern environment?(a) probability of desired patterns(b) probability of given patterns(c) behaviour of system(d) none of the mentionedThis question was addressed to me in an online quiz.This intriguing question originated from Boltzman Machine topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» Correct option is (d) none of the mentioned |
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| 21. |
When activation value is determined by using the average of fluctuations of outputs from other units, it is known as?(a) maximum field approximation(b) median field approximation(c) minimum field approximation(d) none of the mentionedThe question was asked in an interview for internship.My doubt is from Stochastic Networks in portion Feedback Neural Networks of Neural Networks |
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Answer» RIGHT option is (d) none of the mentioned To elaborate: It is KNOWN as MEAN FIELD APPROXIMATION. |
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| 22. |
Where does a stochastic network exhibits stable states ?(a) at any temperature(b) above critical temperature(c) at critical temperature(d) below critical temperatureThe question was posed to me by my school teacher while I was bunking the class.Origin of the question is Stochastic Networks in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct ANSWER is (d) below critical TEMPERATURE |
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| 23. |
Can networks with symmetric weight reach thermal equilibrium?(a) yes(b) noI have been asked this question in unit test.The doubt is from Stochastic Networks topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» Correct OPTION is (a) yes |
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| 24. |
What can be the possible reason for thermal equilibrium in stochastic networks?(a) probability distribution of states changes and compensates(b) probability distribution change with only update(c) probability distribution does not change with time(d) none of the mentionedstochastic network exhibits stable statesThis question was posed to me in an internship interview.I would like to ask this question from Stochastic Networks in section Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT answer is (C) probability distribution does not change with time |
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| 25. |
Is it possible in stochastic network that average state of network doesn’t change with time?(a) yes(b) noI had been asked this question in a national level competition.The doubt is from Stochastic Networks in division Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT OPTION is (a) yes |
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| 26. |
In case of stochastic update, what kind of equilibrium is reached?(a) static(b) dynamic(c) neutral(d) equilibrium not possibleThe question was posed to me in a job interview.I need to ask this question from Stochastic Networks in division Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT OPTION is (b) DYNAMIC |
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| 27. |
In case of stochastic update, can static equilibrium be reached?(a) yes(b) noThis question was addressed to me by my college director while I was bunking the class.My query is from Stochastic Networks in chapter Feedback Neural Networks of Neural Networks |
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Answer» Right CHOICE is (B) no |
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| 28. |
In case of deterministic update, what kind of equilibrium is reached?(a) static(b) dynamic(c) neutral(d) none of the mentionedI got this question in semester exam.My enquiry is from Stochastic Networks topic in portion Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT CHOICE is (a) static |
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| 29. |
Does a stochastic network will evolve differently each time it is run?(a) yes(b) noI have been asked this question in a job interview.This interesting question is from Stochastic Networks in division Feedback Neural Networks of Neural Networks |
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Answer» Correct option is (a) yes |
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| 30. |
p(s=1|x) = 1/(1+exp(-x/T))) ,where ‘s’ is the output given the activation ‘x’ is a?(a) hopfield network(b) sigma network(c) stochastic network(d) noneof the mentionedThe question was asked by my college professor while I was bunking the class.The above asked question is from Stochastic Networks in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct CHOICE is (c) stochastic network |
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| 31. |
Why does change in temperature doesn’t effect stochastic update?(a) shape landscape depends on the network and its weights which varies accordingly and compensates the effect(b) shape landscape depends on the network and its weights which is fixed(c) shape landscape depends on the network, its weights and the output function which varies accordingly and compensates the effect(d) shape landscape depends on the network, its weights and the output function which is fixedI had been asked this question in class test.My question is from Hopfield Model-2 in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct choice is (d) SHAPE landscape DEPENDS on the network, its weights and the OUTPUT function which is fixed |
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| 32. |
As temperature increase, what happens to stochastic update?(a) increase in update(b) decrease in update(c) no change(d) none of the mentionedI have been asked this question by my college professor while I was bunking the class.Query is from Hopfield Model-2 in portion Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT ANSWER is (C) no change |
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| 33. |
How can error in recall due to false minima be further reduced?(a) using suitable activation dynamics(b) cannot be further reduced(c) by storing desired patterns at energy maxima(d) none of the mentionedThis question was addressed to me by my school principal while I was bunking the class.I'm obligated to ask this question of Hopfield Model-2 in division Feedback Neural Networks of Neural Networks |
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Answer» Correct choice is (a) using suitable activation DYNAMICS |
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| 34. |
If connections are not symmetric then basins of attraction may correspond to oscillatory or stable regions, is that true?(a) yes(b) noI got this question during an interview for a job.I'd like to ask this question from Hopfield Model-1 topic in portion Feedback Neural Networks of Neural Networks |
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Answer» Correct choice is (B) no |
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| 35. |
Pattern storage problem which cannot be represented by a feedback network of given size can be called as?(a) easy problems(b) hard problems(c) no such problem exist(d) none of the mentionedThis question was addressed to me at a job interview.I'd like to ask this question from Hopfield Model-2 in division Feedback Neural Networks of Neural Networks |
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Answer» Right CHOICE is (b) hard problems |
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| 36. |
What is the other way to reduce error in recall due to false minima apart from stochastic update?(a) no other method exist(b) by storing desired patterns at lowest energy minima(c) by storing desired patterns at energy maxima(d) none of the mentionedThe question was asked in my homework.The above asked question is from Hopfield Model-2 topic in division Feedback Neural Networks of Neural Networks |
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Answer» Correct ANSWER is (b) by storing desired patterns at lowest ENERGY MINIMA |
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| 37. |
Energy at each state in hopfield with symmetric weights network may increase or decrease?(a) yes(b) noThe question was posed to me during an online interview.Question is from Hopfield Model-2 in division Feedback Neural Networks of Neural Networks |
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Answer» CORRECT ANSWER is (b) no The explanation is: ENERGY of the network cant INCREASE as it MAY then lead to instability. |
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| 38. |
How can error in recall due to false minima be reduced?(a) deterministic update for states(b) stochastic update for states(c) not possible(d) none of the mentionedThe question was posed to me during a job interview.This interesting question is from Hopfield Model-2 topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct option is (b) stochastic UPDATE for STATES |
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| 39. |
Can error in recall due to false minima be reduced?(a) yes(b) noI have been asked this question during an online exam.Origin of the question is Hopfield Model-2 in division Feedback Neural Networks of Neural Networks |
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Answer» Correct ANSWER is (a) yes |
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| 40. |
In hopfield network with symmetric weights, energy at each state may?(a) increase(b) decrease(c) decrease or remain same(d) decrease or increaseI have been asked this question in examination.This key question is from Hopfield Model-2 topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» CORRECT choice is (C) DECREASE or remain same For explanation: ENERGY of the network cant increase as it may then LEAD to instability. |
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| 41. |
In hopfield model with symmetric weights, network can move to?(a) lower(b) higher(c) lower or higher(d) lower or sameI got this question in an online interview.Origin of the question is Hopfield Model-2 in chapter Feedback Neural Networks of Neural Networks |
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Answer» Correct option is (d) lower or same |
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| 42. |
What is gradient descent?(a) method to find the absolute minimum of a function(b) method to find the absolute maximum of a function(c) maximum or minimum, depends on the situation(d) none of the mentionedThis question was posed to me in homework.My question comes from Hopfield Model-1 in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct ANSWER is (a) method to find the absolute MINIMUM of a function |
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| 43. |
For analysis of storage capacity what are the conditions imposed on hopfield model?(a) symmetry of weights(b) asynchronous update(c) symmetry of weights and asynchronous update(d) none of the mentionedThe question was posed to me during an interview.This intriguing question originated from Hopfield Model-1 in portion Feedback Neural Networks of Neural Networks |
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Answer» CORRECT answer is (c) symmetry of WEIGHTS and ASYNCHRONOUS update Easy EXPLANATION: For analysis of storage capacity, symmetry of weights and asynchronous update CONDITIONS are imposed on hopfield model. |
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| 44. |
Asynchronous update ensures that the next state is atmost unit hamming distance from current state, is that true?(a) yes(b) noThe question was posed to me in exam.This question is from Hopfield Model-1 topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» Right option is (a) yes |
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| 45. |
If pattern is to be stored, then what does stable state should have updated value of?(a) current sate(b) next state(c) both current and next state(d) none of the mentionedI had been asked this question by my school principal while I was bunking the class.This is a very interesting question from Hopfield Model-1 in portion Feedback Neural Networks of Neural Networks |
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Answer» Correct answer is (a) CURRENT sate |
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| 46. |
If connections are not symmetric then basins of attraction may correspond to?(a) oscillatory regions(b) stable regions(c) chaotic regions(d) oscillatory or chaotic regionsI got this question during an interview.The doubt is from Hopfield Model-1 in division Feedback Neural Networks of Neural Networks |
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Answer» CORRECT option is (d) OSCILLATORY or chaotic regions To explain: If connections are not SYMMETRIC then basins of attraction may CORRESPOND to oscillatory or chaotic regions. |
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| 47. |
For symmetric weights there exist?(a) basins of attraction corresponding to energy minimum(b) false wells(c) fluctuations in energy landscape(d) none of he mentionedI got this question in a national level competition.The origin of the question is Hopfield Model-1 in portion Feedback Neural Networks of Neural Networks |
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Answer» Correct OPTION is (a) basins of attraction corresponding to ENERGY minimum |
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| 48. |
What is asynchronous update in hopfield model?(a) all units are updated simultaneously(b) a unit is selected at random andits new state is computed(c) a predefined unit is selected and its new state is computed(d) none of the mentionedThe question was asked in class test.I'd like to ask this question from Hopfield Model-1 in chapter Feedback Neural Networks of Neural Networks |
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Answer» The correct answer is (b) a unit is SELECTED at random andits NEW STATE is computed |
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| 49. |
How can states of units be updated in hopfield model?(a) synchronously(b) asynchronously(c) synchronously and asynchronously(d) none of the mentionedThis question was addressed to me in a job interview.This key question is from Hopfield Model-1 in chapter Feedback Neural Networks of Neural Networks |
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Answer» The CORRECT answer is (c) synchronously and asynchronously |
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| 50. |
What is synchronous update in hopfield model?(a) all units are updated simultaneously(b) a unit is selected at random andits new state is computed(c) a predefined unit is selected and its new state is computed(d) none of the mentionedI have been asked this question in an online interview.The above asked question is from Hopfield Model-1 topic in chapter Feedback Neural Networks of Neural Networks |
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Answer» Right choice is (a) all UNITS are updated SIMULTANEOUSLY |
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