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.
| 51. |
How is pattern information distributed?(a) it is distributed all across the weights(b) it is distributed in localised weights(c) it is distributedin certain proctive weights only(d) none of the mentionedThe question was posed to me by my college professor while I was bunking the class.My question is based upon Learning Basics in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» CORRECT option is (a) it is distributed all ACROSS the weights Easy explanation: PATTERN information is HIGHLY distributed all across the weights. |
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| 52. |
What are the requirements of learning laws?(a) learning should be able to capture more & more patterns(b) learning should be able to grasp complex nonliear mappings(c) convergence of weights(d) all of the mentionedI have been asked this question by my school principal while I was bunking the class.My doubt is from Learning Basics topic in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» The correct answer is (d) all of the mentioned |
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| 53. |
Memory decay affects what kind of memory?(a) short tem memory in general(b) older memory in general(c) can be short term or older(d) none of the mentionedI got this question by my college professor while I was bunking the class.Origin of the question is Learning Basics topic in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» The correct answer is (a) short tem MEMORY in general |
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| 54. |
What are the requirements of learning laws?(a) convergence of weights(b) learning time should be as small as possible(c) learning should use only local weights(d) all of the mentionedThe question was asked by my college director while I was bunking the class.I'm obligated to ask this question of Learning Basics in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right OPTION is (d) all of the mentioned |
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| 55. |
If xb(t) represents differentiation of state x(t), then a stochastic model can be represented by?(a) xb(t)=deterministic model(b) xb(t)=deterministic model + noise component(c) xb(t)=deterministic model*noise component(d) none of the mentioned’This question was posed to me in class test.My query is from Learning Basics topic in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» The CORRECT choice is (B) xb(t)=deterministic MODEL + noise component |
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| 56. |
Learning is a?(a) slow process(b) fast process(c) can be slow or fast in general(d) can’t sayThis question was addressed to me in exam.This interesting question is from Learning Basics in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT option is (a) SLOW process The BEST I can explain: LEARNING is a slow process. |
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| 57. |
What is the condition in Stochastic models, if xb(t) represents differentiation of state x(t)?(a) xb(t)=0(b) xb(t)=1(c) xb(t)=n(t), where n is noise component(d) xb(t)=n(t)+1This question was posed to me during an interview for a job.Origin of the question is Learning Basics in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct OPTION is (c) xb(t)=n(t), where n is noise component |
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| 58. |
What is asynchronous update in a network?(a) update to all units is done at the same time(b) change in state of any one unit drive the whole network(c) change in state of any number of units drive the whole network(d) none of the mentionedI got this question in final exam.Origin of the question is Learning Basics in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT CHOICE is (b) change in STATE of any one unit DRIVE the whole NETWORK The best explanation: In asynchronous update, change in state of any one unit drive the whole network. |
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| 59. |
What is equilibrium in neural systems?(a) deviation in present state, when small perturbations occur(b) settlement of network, when small perturbations occur(c) change in state, when small perturbations occur(d) none of the mentionedI got this question by my school principal while I was bunking the class.This question is from Learning Basics in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» The CORRECT CHOICE is (B) settlement of network, when small perturbations occur |
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| 60. |
Activation models are?(a) dynamic(b) static(c) deterministic(d) none of the mentionedThis question was posed to me in an interview for internship.My enquiry is from Learning Basics in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» CORRECT choice is (C) deterministic Explanation: Input/output patterns & the activation VALUES may be considered as sample functions of RANDOM PROCESS. |
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| 61. |
Who proposed the shunting activation model?(a) rosenblatt(b) hopfield(c) perkel(d) grossbergThe question was asked in a national level competition.My doubt is from Activation Models in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» CORRECT option is (d) GROSSBERG The EXPLANATION is: Grossberg proposed the MODEL in 1982. |
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| 62. |
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 inputsI have been asked this question in an interview.This key question is from Activation Models in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct option is (b) to keep operating range of ACTIVATION VALUE to a SPECIFIED range |
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| 63. |
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^2(c) f(x)=x^3(d) none of the mentionedI have been asked this question during an internship interview.My question is from Activation Models in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT OPTION is (a) F(x)=x For explanation: Perkels MODEL assumes output function to be LINEAR. |
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| 64. |
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 mentionedThis question was posed to me in a national level competition.I need to ask this question from Activation Models topic in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT choice is (B) ADDITIVE & shunting activation MODELS The best I can explain: Additive & shunting activation models are the most basic category of activation models. |
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| 65. |
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 mentionedThe question was posed to me in examination.Question is taken from Activation Models topic in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right answer is (a) when both synaptic & ACTIVATION dynamics are simultaneously used & are in equilibrium |
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| 66. |
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 mentionedI had been asked this question in a national level competition.I want to ask this question from Activation Models in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right option is (d) none of the mentioned |
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| 67. |
Broadly how many kinds of stability can be defined in neural networks?(a) 1(b) 3(c) 2(d) 4The question was posed to me in an international level competition.My query is from Activation Models in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct CHOICE is (c) 2 |
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| 68. |
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 mentionedI have been asked this question in an interview.This question is from Activation Models topic in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right ANSWER is (d) none of the mentioned |
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| 69. |
What is noise saturation dilemma?(a) at saturation state neuron willstop 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 mentionedThe question was posed to me during an online exam.Question is taken from Activation Models in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right choice is (B) how can a neuron with LIMITED OPERATING range be made sensitive to nearly unlimited range of inputs |
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| 70. |
In activation dynamics is output function bounded?(a) yes(b) noThis question was posed to me in quiz.This question is from Activation Models topic in section Activation and Synaptic Dynamics of Neural Networks |
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Answer» CORRECT choice is (a) yes The explanation is: It is the NATURE of output FUNCTION in activation DYNAMICS. |
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| 71. |
Activation value is associated with?(a) potential at synapses(b) cell membrane potential(c) all of the mentioned(d) none of the mentionedI have been asked this question in a national level competition.Asked question is from Activation Models in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct CHOICE is (B) CELL membrane potential |
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| 72. |
What kind of dynamics leads to learning laws?(a) synaptic(b) neural(c) activation(d) both synaptic & neuralI got this question in an international level competition.This is a very interesting question from Dynamics in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» The CORRECT CHOICE is (a) synaptic |
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| 73. |
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 mentionedI had been asked this question by my college director while I was bunking the class.I want to ask this question from Dynamics in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct OPTION is (C) both way |
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| 74. |
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 mentionedThe question was asked in an online interview.I would like to ask this question from Dynamics in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT choice is (b) the ABILITY of a pattern recognition system to approximate the desired OUTPUT values for pattern vectors which are not in the training set. For explanation: Follows from BASIC definition of generalization. |
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| 75. |
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 mentionedThis question was posed to me in homework.Question is taken from Dynamics in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» Correct CHOICE is (b) deciding what class an input pattern BELONGS to |
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| 76. |
Synaptic dynamics is referred as?(a) short term memory(b) long term memory(c) either short or long term(d) both short & long termThe question was posed to me in final exam.This intriguing question comes from Dynamics topic in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» The CORRECT answer is (B) long term memory |
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| 77. |
Activation dynamics is referred as?(a) short term memory(b) long term memory(c) either short or long term(d) both short & long termThis question was posed to me in exam.This question is from Dynamics topic in division Activation and Synaptic Dynamics of Neural Networks |
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Answer» RIGHT CHOICE is (a) short term memory For explanation I would say: It DEPENDS on input pattern, & input CHANGES from moment to moment, HENCE Short term memory. |
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| 78. |
During activation dynamics does weight changes?(a) yes(b) noThis question was addressed to me during a job interview.My question is from Dynamics topic in portion Activation and Synaptic Dynamics of Neural Networks |
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Answer» The CORRECT CHOICE is (B) no |
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| 79. |
Which is faster neural level dynamics or synaptic dynamics?(a) neural level(b) synaptic(c) both equal(d) insufficient informationThis question was posed to me during an online interview.Origin of the question is Dynamics topic in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» Right choice is (a) NEURAL level |
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| 80. |
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 mentionedI had been asked this question during an interview.My enquiry is from Dynamics in chapter Activation and Synaptic Dynamics of Neural Networks |
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Answer» The correct CHOICE is (a) synaptic DYNAMICS |
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