Last updated on June 12th, 2025
De Morgan’s Law is a pair of rules in Boolean algebra, logic, and set theory. It relates the intersection and union of sets through complements. De Morgan’s Law is applied in the fields of mathematics, computer science, and design. In this article, we will learn more about De Morgan’s Law.
De Morgan’s Law explains how union, intersection, and complements are connected in set theory. In Boolean algebra, it shows how AND, OR, and NOT interact with each other. In logic, it shows the relationship between AND, OR, and NEGATION of the statement. De Morgan’s Law helps in optimizing various Boolean expressions and circuit designs.
De Morgan’s Laws:
In Logic (Boolean Algebra & Logic):
The negation of a disjunction (OR) is the conjunction (AND) of the negations:
¬(A ∨ B) = ¬A ∧ ¬B
¬(A ∨ B) = ¬A ∧ ¬B
Negating an AND statement turns it into an OR statement with each term negated:
¬(A ∧ B) = ¬A ∨ ¬B
¬(A ∧ B) = ¬A ∨ ¬B
In Set Theory:
The complement of a union is the intersection of the individual complements:
(A ∪ B)’ = A’ ∩ B’
(A ∪ B)’ = A’ ∩ B’
The complement of an intersection is the union of the individual complements:
(A ∩ B)’ = A’ ∪ B’
(A ∩ B)’ = A’ ∪ B’
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De Morgan’s Law says that negating a combined expression distributes the negation to each individual part while switching the AND/OR operation.
De Morgan’s Law in set theory describes how complements interact with union (OR) and intersection (AND). These laws help simplify expressions in probability and logic.
There are two laws in Set theory:
First law: Complement of Union
(A ∪ B)’ = A’ ∩ B’
The complement of the union is the intersection of their individual complements.
Second law: Complement of Intersection
(A ∩ B)’ = A’ ∪ B’
The complement of the intersection of two sets is the union of their individual complements.
In Boolean algebra, De Morgan’s Law explains how the NOT operation interacts with AND and OR. These laws are crucial in designing logical circuits as they help simplify Boolean expressions.
The two laws in De Morgan’s Law state that:
The first law: Negation of OR
(A + B)’ = A’ . B’
This means that the negation or complement of A OR B is equal to NOT A AND NOT B.
The second law: The Negation of AND
(AB)’ = A’ + B’
This means that the negation or complement of A AND B is equal to NOT A OR NOT B.
De Morgan’s Law is used in Boolean algebra because it simplifies Boolean expressions and makes conversions between NAND and NOR gates easy.
Let us learn more about De Morgan’s formulas in set theory, Boolean algebra, and logic.
In set theory:
Where:
In Logic:
Where:
De Morgan’s Law can be quite overwhelming as there are many rules to remember. This may lead to students making mistakes. Here are a few common mistakes students make and ways to avoid them:
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De Morgan’s law is widely used in several fields mainly computer science. Here are some real-world uses of De Morgan’s Law:
Simplify the logical expression ¬ ( A ∧ B ).
¬ A ∨ ¬ B
De Morgan’s Law states that the negation of an AND is equivalent to the OR of the negations: ¬ (A ∧ B) = ¬ A ∨ ¬ B.
Express the complement of the intersection of sets A and B in terms of Ac and Bc
(A ∩ B )c = Ac ∪ Bc.
De Morgan’s Law states that the complement of an intersection is the union of the complements.
Express the complement of the union of sets A and B in terms of A^c and B^c
(A∪B)c = Ac ∩ Bc.
In sets, the complement of a union is given by the intersection of the complements.
Express the complement of the union of sets A, B, and C in terms of their complements.
(A ∪ B ∪ C)c = Ac ∩ Bc ∩ Cc.
De Morgan’s law generalizes to multiple sets: the complement of a union equals the intersection of the complements.
Simplify the Boolean expression ¬((X ∧ Y) ∨ Z).
( ¬ X ∨ ¬ Y) ∧ ¬ Z.
First, apply De Morgan’s Law to the outer OR:
¬((X ∧ Y) ∨ Z) = ¬(X ∧ Y) ∧ ¬Z ¬((X ∧ Y) ∨ Z) = ¬(X ∧ Y) ∧ ¬Z.
Then, simplify ¬(X ∧ Y) = ¬X ∨ ¬Y ¬(X ∧ Y) = ¬X ∨ ¬Y.
Thus the final result is: ( ¬ X ∨ ¬ Y) ∧ ¬ Z.
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Jaipreet Kour Wazir is a data wizard with over 5 years of expertise in simplifying complex data concepts. From crunching numbers to crafting insightful visualizations, she turns raw data into compelling stories. Her journey from analytics to education ref
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