gs gs127 Activation and Synaptic Dynamics - Learning Basics - Quiz No.1
gs gs127 SQLite Quiz
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Question 1: Activation models are?
dynamic
static
deterministic
none of the mentioned
Question 2: If xb(t) represents differentiation of state x(t), then a stochastic model can be represented by?
xb(t)=deterministic model
xb(t)=deterministic model + noise component
xb(t)=deterministic model*noise component
none of the mentioned’
Question 3: What is equilibrium in neural systems?
deviation in present state, when small perturbations occur
settlement of network, when small perturbations occur
change in state, when small perturbations occur
none of the mentioned
Question 4: What is the condition in Stochastic models, if xb(t) represents differentiation of state x(t)?
xb(t)=0
xb(t)=1
xb(t)=n(t), where n is noise component
xb(t)=n(t)+1
Question 5: What is asynchronous update in a network?
update to all units is done at the same time
change in state of any one unit drive the whole network
change in state of any number of units drive the whole network
none of the mentioned
Question 6: Learning is a?
slow process
fast process
can be slow or fast in general
can’t say
Question 7: What are the requirements of learning laws?
convergence of weights
learning time should be as small as possible
learning should use only local weights
all of the mentioned
Question 8: Memory decay affects what kind of memory?
short tem memory in general
older memory in general
can be short term or older
none of the mentioned
Question 9: What are the requirements of learning laws?
learning should be able to capture more & more patterns
learning should be able to grasp complex nonliear mappings
convergence of weights
all of the mentioned
Question 10: How is pattern information distributed?
it is distributed all across the weights
it is distributed in localised weights
it is distributed in certain proctive weights only
none of the mentioned
Question 11: What is supervised learning?
weight adjustment based on deviation of desired output from actual output
weight adjustment based on desired output only
weight adjustment based on actual output only
none of the mentioned
Question 12: Supervised learning may be used for?
temporal learning
structural learning
both temporal & structural learning
none of the mentioned
Question 13: What is structural learning?
concerned with capturing input-output relationship in patterns
concerned with capturing weight relationships
both weight & input-output relationships
none of the mentioned
Question 14: What is temporal learning?
concerned with capturing input-output relationship in patterns
concerned with capturing weight relationships
both weight & input-output relationships
none of the mentioned
Question 15: What is unsupervised learning?
weight adjustment based on deviation of desired output from actual output
weight adjustment based on desired output only
weight adjustment based on local information available to weights
none of the mentioned
Question 18: What is nature of input in activation dynamics?
static
dynamic
both static & dynamic
none of the mentioned
Question 20: what does the term wij(0) represents in synaptic dynamic model?
a prioi knowledge
just a constant
no strong significance
future adjustments
