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Welcome to the Neural Networks MCQs Page

Dive deep into the fascinating world of Neural Networks with our comprehensive set of Multiple-Choice Questions (MCQs). This page is dedicated to exploring the fundamental concepts and intricacies of Neural Networks, a crucial aspect of UGC CBSE NET Exam. In this section, you will encounter a diverse range of MCQs that cover various aspects of Neural Networks, from the basic principles to advanced topics. Each question is thoughtfully crafted to challenge your knowledge and deepen your understanding of this critical subcategory within UGC CBSE NET Exam.

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Check out the MCQs below to embark on an enriching journey through Neural Networks. Test your knowledge, expand your horizons, and solidify your grasp on this vital area of UGC CBSE NET Exam.

Note: Each MCQ comes with multiple answer choices. Select the most appropriate option and test your understanding of Neural Networks. You can click on an option to test your knowledge before viewing the solution for a MCQ. Happy learning!

Neural Networks MCQs | Page 1 of 2

Q1.
Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes.
Discuss
Answer: (b).Backward from sink to source
Q2.
Identify the following activation function :
φ(V) = Z + (1/ 1 + exp (– x * V + Y) ),
Z, X, Y are parameters 
Discuss
Answer: (c).Sigmoid function
Q3.
An artificial neuron receives n inputs x1, x2, x3............xn with  weights w1, w2, ..........wn attached to the input links. The weighted sum_________________ is computed to be passed on to a non-linear filter  Φ called activation function to release the output.
Discuss
Answer: (d).Σ wi* xi
Q4.
Match the following knowledge representation techniques with their applications:

List – I List – II

(a) Frames (i) Pictorial representation of objects, their attributes and relationships

(b) Conceptual dependencies (ii) To describe real world stereotype events

(c) Associative networks (iii) Record like structures for grouping closely related knowledge

(d) Scripts (iv) Structures and primitives to represent sentences

code:
a b c d
Discuss
Answer: (a).(iii) (iv) (i) (ii)
Q5.
In propositional logic P ⇔ Q is equivalent to (Where ~ denotes NOT):
Discuss
Answer: (b).(~ P ˅ Q) ˄ (~ Q ˅ P)
Q6.
Slots and facets are used in
Discuss
Answer: (b).Frames
Q7.
A neuron with 3 inputs has the weight vector [0.2 -0.1 0.1]^T and a bias θ = 0. If the input vector is X = [0.2 0.4 0.2]^T then the total input to the neuron is:
Discuss
Answer: (c).0.02
Q8.
Which of the following neural networks uses supervised learning?

(A) Multilayer perceptron
(B) Self organizing feature map
(C) Hopfield network
Discuss
Answer: (a).(A) only
Q9.
Consider the following statements:

(a) If primal (dual) problem has a finite optimal solution, then its dual (primal) problem has a finite optimal solution.
(b) If primal (dual) problem has an unbounded optimum solution, then its dual (primal) has no feasible solution at all.
(c) Both primal and dual problems may be infeasible.
Which of the following is correct?
Discuss
Answer: (d).(a), (b) and (c)
Q10.
Consider the following statements :

(a) Assignment problem can be used to minimize the cost.
(b) Assignment problem is a special case of transportation problem.
(c) Assignment problem requires that only one activity be assigned to each resource.

Which of the following options is correct?
Discuss
Answer: (d).(a), (b) and (c)
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