1. what is estimated density of neuron per mm^2 of cortex?
a) 15*(102)
b) 15*(104)
c) 15*(103)
d) 5*(104)
Explanation: It is a biological fact !
2. Why can’t we design a perfect neural network?
a) full operation is still not known of biological neurons
b) number of neuron is itself not precisely known
c) number of interconnection is very large & is very complex
d) all of the mentioned
Explanation:These are all fundamental reasons, why can’t we design a perfect neural network !
3. How many synaptic connection are there in human brain?
a) 1010
b) 1015
c) 1020
d) 105
Explanation: You can estimate this value from number of neurons in human cortex & their density.
4. Operations in the neural networks can perform what kind of operations?
a) serial
b) parallel
c) serial or parallel
d) none of the mentioned
Explanation: General characteristics of neural networks
5. Does the argument information in brain is adaptable, whereas in the computer it is replaceable is valid?
a) yes
b) no
Explanation: Its a fact & related to basic knowledge of neural networks !
6. Does there exist central control for processing information in brain as in computer?
a) yes
b) no
Explanation: In human brain information is locally processed & analysed.
7. Which action is faster pattern classification or adjustment of weights in neural nets?
a) pattern classification
b) adjustment of weights
c) equal
d) either of them can be fast, depending on conditions
Explanation: Memory is addressable, so thus pattern can be easily classified.
8. What is the feature of ANNs due to which they can deal with noisy, fuzzy, inconsistent data?
a) associative nature of networks
b) distributive nature of networks
c) both associative & distributive
d) none of the mentioned
Explanation: General characteristics of ANNs
9. What was the name of the first model which can perform wieghted sum of inputs?
a) McCulloch-pitts neuron model
b) Marvin Minsky neuron model
c) Hopfield model of neuron
d) none of the mentioned
Explanation: McCulloch-pitts neuron model can perform weighted sum of inputs followed by threshold logic operation
10. Who developed the first learning machine in which connection strengths could be adapted automatically?
a) McCulloch-pitts
b) Marvin Minsky
c) Hopfield
d) none of the mentioned
Explanation: In 1954 Marvin Minsky developed the first learning machine in which connection strengths could be adapted automatically & efficiebtly.