Skip to main content

Simplification Of Boolean Functions


Simplification Using Algebraic Functions

In this approach, one Boolean expression is minimized into an equivalent expression by applying Boolean identities.

Problem 1

Minimize the following Boolean expression using Boolean identities −
F(A,B,C)=AB+BC+BC+ABC

Solution

Given,F(A,B,C)=AB+BC+BC+ABC
Or,F(A,B,C)=AB+(BC+BC)+BC+ABC
[By idempotent law, BC’ = BC’ + BC’]
Or,F(A,B,C)=AB+(BC+BC)+(BC+ABC)
Or,F(A,B,C)=AB+B(C+C)+C(B+AB)
[By distributive laws]
Or,F(A,B,C)=AB+B.1+C(B+A)
[ (C' + C) = 1 and absorption law (B + AB')= (B + A)]
Or,F(A,B,C)=AB+B+C(B+A)
[ B.1 = B ]
Or,F(A,B,C)=B(A+1)+C(B+A)
Or,F(A,B,C)=B.1+C(B+A)
[ (A' + 1) = 1 ]
Or,F(A,B,C)=B+C(B+A)
[ As, B.1 = B ]
Or,F(A,B,C)=B+BC+AC
Or,F(A,B,C)=B(1+C)+AC
Or,F(A,B,C)=B.1+AC
[As, (1 + C') = 1]
Or,F(A,B,C)=B+AC
[As, B.1 = B]
So,F(A,B,C)=B+ACis the minimized form.

Problem 2

Minimize the following Boolean expression using Boolean identities −
F(A,B,C)=(A+B)(B+C)

Solution

Given, F(A,B,C)=(A+B)(A+C)
Or, F(A,B,C)=A.A+A.C+B.A+B.C [Applying distributive Rule]
Or, F(A,B,C)=A+A.C+B.A+B.C [Applying Idempotent Law]
Or, F(A,B,C)=A(1+C)+B.A+B.C [Applying distributive Law]
Or, F(A,B,C)=A+B.A+B.C [Applying dominance Law]
Or, F(A,B,C)=(A+1).A+B.C [Applying distributive Law]
Or, F(A,B,C)=1.A+B.C [Applying dominance Law]
Or, F(A,B,C)=A+B.C [Applying dominance Law]
So, F(A,B,C)=A+BC is the minimized form.

Karnaugh Maps

The Karnaugh map (K–map), introduced by Maurice Karnaughin in 1953, is a grid-like representation of a truth table which is used to simplify boolean algebra expressions. A Karnaugh map has zero and one entries at different positions. It provides grouping together Boolean expressions with common factors and eliminates unwanted variables from the expression. In a K-map, crossing a vertical or horizontal cell boundary is always a change of only one variable.

Example 1

An arbitrary truth table is taken below −
ABA operation B
00w
01x
10y
11z
Now we will make a k-map for the above truth table −
K-map 1

Example 2

Now we will make a K-map for the expression − AB+ A’B’
K-map 2

Simplification Using K-map

K-map uses some rules for the simplification of Boolean expressions by combining together adjacent cells into single term. The rules are described below −
Rule 1 − Any cell containing a zero cannot be grouped.
K- map Rule 1
Wrong grouping
Rule 2 − Groups must contain 2n cells (n starting from 1).
K- map Rule 2
Wrong grouping
Rule 3 − Grouping must be horizontal or vertical, but must not be diagonal.
K- map Rule3
Wrong diagonal grouping
K- map Rule 3
Proper vertical grouping
K- map Rule 3
Proper horizontal grouping
Rule 4 − Groups must be covered as largely as possible.
K- map Rule 4
Insufficient grouping
K- map Rule 4
Proper grouping
Rule 5 − If 1 of any cell cannot be grouped with any other cell, it will act as a group itself.
K- map Rule 5
Proper grouping
Rule 6 − Groups may overlap but there should be as few groups as possible.
K- map Rule 6
Proper grouping
Rule 7 − The leftmost cell/cells can be grouped with the rightmost cell/cells and the topmost cell/cells can be grouped with the bottommost cell/cells.
K- map Rule 7
Proper grouping

Problem

Minimize the following Boolean expression using K-map −
F(A,B,C)=ABC+ABC+ABC+ABC

Solution

Each term is put into k-map and we get the following −
K-map Problem 1
K-map for F (A, B, C)
Now we will group the cells of 1 according to the rules stated above −
K-map Problem 2
K-map for F (A, B, C)
We have got two groups which are termed as AB and AB. Hence, F(A,B,C)=AB+AB=AB. It is the minimized form.

Comments

Popular posts from this blog

Discrete Mathematics - Rules of Inference

To deduce new statements from the statements whose truth that we already know,  Rules of Inference  are used. What are Rules of Inference for? Mathematical logic is often used for logical proofs. Proofs are valid arguments that determine the truth values of mathematical statements. An argument is a sequence of statements. The last statement is the conclusion and all its preceding statements are called premises (or hypothesis). The symbol “ ∴ ∴ ”, (read therefore) is placed before the conclusion. A valid argument is one where the conclusion follows from the truth values of the premises. Rules of Inference provide the templates or guidelines for constructing valid arguments from the statements that we already have. Table of Rules of Inference Rule of Inference Name Rule of Inference Name P ∴ P ∨ Q P ∴ P ∨ Q Addition P ∨ Q ¬ P ∴ Q P ∨ Q ¬ P ∴ Q Disjunctive Syllogism P Q ∴ P ∧ Q P Q ∴ P ∧ Q Conjunction P → Q Q → R ∴ P → R P → Q Q → R ∴ P → R ...

Digital Circuits - Shift Registers

We know that one flip-flop can store one-bit of information. In order to store multiple bits of information, we require multiple flip-flops. The group of flip-flops, which are used to hold (store) the binary data is known as  register . If the register is capable of shifting bits either towards right hand side or towards left hand side is known as  shift register . An ‘N’ bit shift register contains ‘N’ flip-flops. Following are the four types of shift registers based on applying inputs and accessing of outputs. Serial In − Serial Out shift register Serial In − Parallel Out shift register Parallel In − Serial Out shift register Parallel In − Parallel Out shift register Serial In − Serial Out (SISO) Shift Register The shift register, which allows serial input and produces serial output is known as Serial In – Serial Out  (SISO)  shift register. The  block diagram  of 3-bit SISO shift register is shown in the following figure. This block d...

discrete mathematics: Venn Diagrams

Venn Diagrams Venn diagram, invented in 1880 by John Venn, is a schematic diagram that shows all possible logical relations between different mathematical sets. Examples Set Operations Set Operations include Set Union, Set Intersection, Set Difference, Complement of Set, and Cartesian Product. Set Union The union of sets A and B (denoted by  A ∪ B A ∪ B ) is the set of elements which are in A, in B, or in both A and B. Hence,  A ∪ B = { x | x ∈ A   O R   x ∈ B } A ∪ B = { x | x ∈ A   O R   x ∈ B } . Example  − If  A = { 10 , 11 , 12 , 13 } A = { 10 , 11 , 12 , 13 }  and B =  { 13 , 14 , 15 } { 13 , 14 , 15 } , then  A ∪ B = { 10 , 11 , 12 , 13 , 14 , 15 } A ∪ B = { 10 , 11 , 12 , 13 , 14 , 15 } . (The common element occurs only once) Set Intersection The intersection of sets A and B (denoted by  A ∩ B A ∩ B ) is the set of elements which are in both A and B. Hence,  A ∩ B = { x | x ∈ A   A N D...