Minimization | Digital Logic - Computer Science Engineering (CSE) PDF Download

K-Map (Karnaugh Map)

In many digital circuits and practical problems we need to find expression with minimum variables. We can minimize Boolean expressions of 3, 4 variables very easily using K-map without using any Boolean algebra theorems. K-map can take two forms Sum of Product (SOP) and Product of Sum (POS) according to the need of problem. K-map is table like representation but it gives more information than TRUTH TABLE. We fill grid of K-map with 0’s and 1’s then solve it by making groups.

Steps to solve expression using K-map-

  1. Select K-map according to the number of variables.
  2. Identify minterms or maxterms as given in problem.
  3. For SOP put 1’s in blocks of K-map respective to the minterms (0’s elsewhere).
  4. For POS put 0’s in blocks of K-map respective to the maxterms(1’s elsewhere).
  5. Make rectangular groups containing total terms in power of two like 2,4,8 ..(except 1) and try to cover as many elements as you can in one group.
  6. From the groups made in step 5 find the product terms and sum them up for SOP form.

SOP FORM

  1. K-map of 3 variables-

Z= ∑A,B,C(1,3,6,7)

Minimization | Digital Logic - Computer Science Engineering (CSE)

From red group we get product term—

A’C

From green group we get product term—

AB

Summing these product terms  we get- Final expression (A’C+AB)

  1. K-map for 4 variables

F(P,Q,R,S)=∑(0,2,5,7,8,10,13,15)

Minimization | Digital Logic - Computer Science Engineering (CSE)

From red group we get product term—

QS

From green group we get product term—

Q’S’

Summing  these product terms  we get- Final expression (QS+Q’S’)

POS FORM

  1. K-map of 3 variables-

F(A,B,C)=π(0,3,6,7)

Minimization | Digital Logic - Computer Science Engineering (CSE)

From red group we find  terms

A    B      C’

Taking complement of these two

A’     B’     C

Now sum up them

(A’ + B’ + C)

From green group we find  terms

B         C

Taking complement of these two terms

B’         C’

Now sum up them

(B’+C’)

From brown group we find terms

A’ B’ C’

Taking complement of these two

A B C

Now sum up them

(A + B + C)

We will take product of these three terms :Final expression (A’ + B’ + C) (B’ + C’) (A + B + C)

2. K-map of  4 variables-

F(A,B,C,D)=π(3,5,7,8,10,11,12,13)

Minimization | Digital Logic - Computer Science Engineering (CSE)

From green group we find  terms

C’     D     B

Taking their complement and summing them

(C+D’+B’)

From red group we find terms

C     D    A’

Taking their complement and summing them

(C’+D’+A)

From blue  group we find  terms

A     C’     D’

Taking their complement and summing them

(A’+C+D)

From brown  group we find  terms

A    B’    C

Taking their complement and summing them

(A’+B+C’)

Finally we express these as product –(C+D’+B’).(C’+D’+A).(A’+C+D).(A’+B+C’)

PITFALL  *Always remember POS ≠ (SOP)’

*The correct form is (POS of F)=(SOP of F’)’

The document Minimization | Digital Logic - Computer Science Engineering (CSE) is a part of the Computer Science Engineering (CSE) Course Digital Logic.
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FAQs on Minimization - Digital Logic - Computer Science Engineering (CSE)

1. What is minimization in Computer Science Engineering (CSE)?
Ans. Minimization in Computer Science Engineering refers to the process of reducing something, such as code, algorithms, or resources, to its simplest or most efficient form. It involves eliminating redundancies, simplifying complex structures, and optimizing performance to improve the overall efficiency of a system.
2. Why is minimization important in Computer Science Engineering (CSE)?
Ans. Minimization is crucial in Computer Science Engineering as it helps in improving the efficiency and performance of systems. By minimizing code, algorithms, or resources, engineers can reduce the memory footprint, decrease computational time, and enhance the overall speed and responsiveness of software applications and systems.
3. How is minimization achieved in Computer Science Engineering (CSE)?
Ans. Minimization in Computer Science Engineering can be achieved through various techniques such as code refactoring, algorithmic optimizations, resource management, and system design improvements. Engineers often analyze the existing code or system, identify bottlenecks or redundancies, and then apply suitable techniques to minimize them and enhance the overall efficiency.
4. What are the benefits of minimization in Computer Science Engineering (CSE)?
Ans. The benefits of minimization in Computer Science Engineering are numerous. It helps in reducing memory usage, improving computational speed, optimizing power consumption, enhancing scalability, and reducing the overall complexity of systems. Minimization also leads to better maintainability, easier debugging, and increased code reusability.
5. Are there any potential drawbacks or challenges in the process of minimization?
Ans. While minimization brings several advantages, it can also introduce certain challenges. One potential drawback is the trade-off between code simplicity and readability. Over-minimization can sometimes make the code difficult to understand or maintain. Additionally, achieving an optimal balance between minimizing resources and preserving functionality can be challenging, requiring careful analysis and testing to ensure the desired results.
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