adplus-dvertising

Discussion Forum

Que. In propositional logic P ⇔ Q is equivalent to (Where ~ denotes NOT):
a. ~ (P ˅ Q) ˄ ~ (Q ˅ P)
b. (~ P ˅ Q) ˄ (~ Q ˅ P)
c. (P ˅ Q) ˄ (Q ˅ P)
d. ~ (P ˅ Q) → ~ (Q ˅ P)
Answer:(~ P ˅ Q) ˄ (~ Q ˅ P)
sandeep16064 :(May 26, 2020) PQ'+P'Q

Complement of this became result
Click Here to Reply
Confused About the Answer? Ask for Details Here
Know Explanation? Add it Here

Similar Questions:

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:
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?
In propositional logic P ⇔ Q is equivalent to (Where ~ denotes NOT):
Which of the following neural networks uses supervised learning?

(A) Multilayer perceptron
(B) Self organizing feature map
(C) Hopfield network
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?
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
Match the following :

(i) OLAP                        (a) Regression
(ii) OLTP                        (b) Data Warehouse
(iii) Decision Tree        (c) RDBMS
(iv) Neural Network     (d) Classification

code:
      (i)   (ii)  (iii)   (iv)
Back propagation is a learning technique that adjusts weights in the neural network by propagating weight changes.
Identify the following activation function :
φ(V) = Z + (1/ 1 + exp (– x * V + Y) ),
Z, X, Y are parameters 
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.
Slots and facets are used in
In Delta Rule for error minimization
Which of the following can be used for clustering of data ?

GATE CSE Resources

Questions from Previous year GATE question papers

UGC NET Computer science Resources

UGC NET Previous year questions and practice sets

NET General Paper 1

UGC NET Previous year questions and practice sets

GATE CSE Online Test

Attempt a small test to analyze your preparation level. This GATE exam includes questions from previous year GATE papers.

UGC NET practice Test

Practice test for UGC NET Computer Science Paper. The questions asked in this NET practice paper are from various previous year papers.