lecture 8: k-map to pos reductions k-maps in higher dimensions · lecture 8: k-map to pos...

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Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital Systems Diba Mirza Dept. of Computer Science and Engineering University of California, San Diego 1

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Page 1: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Lecture 8: K-Map to POS reductions K-maps in higher dimensions

CSE 140: Components and Design Techniques for Digital Systems

Diba Mirza

Dept. of Computer Science and Engineering University of California, San Diego

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Page 2: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Part I. Combinational Logic 1.  Specification 2.  Implementation

K-map: Sum of products Product of sums

2

Page 3: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Implicant: A product term that has non-empty intersection with on-setF and does not intersect with off-set R . Prime Implicant: An implicant that is not a proper subset of any other implicant. Essential Prime Implicant: A prime implicant that has an element in on-set F but this element is not covered by any other prime implicants.

Implicate: A sum term that has non-empty intersection with off-set R and does not intersect with on-set F. Prime Implicate: An implicate that is not a proper subset of any other implicate. Essential Prime Implicate: A prime implicate that has an element in off-set R but this element is not covered by any other prime implicates.

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Page 4: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

K-Map to Minimized Product of Sum

4

• Sometimes easier to reduce the K-map by considering the offset

•  Usually when number of zero outputs is less than number of outputs that evaluate to one OR offset is smaller than onset

ab

cd

00

01

00 01 11 10

11

10

1  1 1 1 0 1 1 1 0 1 1 1 1 1 1 1

Page 5: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Minimum Product of Sum: Ex1

5

Given F (a,b,c) = Σm (3, 5), D = Σm (0, 4)

0 2 6 4

1 3 7 5

X 0 0 X

0 1 0 1

ab c 00 01 11 10

0

1

Page 6: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Minimum Product of Sum: Ex 1

6

Given F (a,b,c) = Σm (3, 5), D = Σm (0, 4)

0 2 6 4

1 3 7 5

X 0 0 X

0 1 0 1

ab c 00 01 11 10

0

1

PI Q: The adjacent cells grouped in red minimize to the following sum term: A. a+b B. (a+b)’ C. a’+b’

Page 7: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Minimum Product of Sum: Ex1

7

Given F (a,b,c) = Σm (3, 5), D = Σm (0, 4)

0 2 6 4

1 3 7 5

X 0 0 X

0 1 0 1

ab c 00 01 11 10

0

1

Prime Implicates: Essential Primes Implicates: Min exp: f(a,b,c) =

Page 8: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Minimum Product of Sum: Ex 1

8

Given F (a,b,c) = Σm (3, 5), D = Σm (0, 4)

0 2 6 4

1 3 7 5

X 0 0 X

0 1 0 1

ab c 00 01 11 10

0

1

Prime Implicates: ΠM (0, 1), ΠM (0, 2, 4, 6), ΠM (6, 7) Essential Primes Implicates: ΠM (0, 1), ΠM (0, 2, 4, 6), ΠM(6, 7) Min exp: f(a,b,c) = (a+b)(c )(a’+b’)

Page 9: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Corresponding Circuit

a

b

a’

b’

c

f(a,b,c,d)

9

Min exp: f(a,b,c) = (a+b)(c )(a’+b’)

Page 10: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

1 0 0 1

1 0 0 X

0 0 0 0

1 0 1 X

10

ab cd

00

01

00 01 11 10

11

10

•  Reduce the following to a POS form •  First find the essential prime implicates

Minimum product of sum: Ex 2

Page 11: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

1 0 0 1

1 0 0 X

0 0 0 0

1 0 1 X

11

ab cd

00

01

00 01 11 10

11

10

•  Reduce the following to a POS form •  First find the essential prime implicates

Minimum product of sum: Ex2

Page 12: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

1 0 0 1

1 0 0 X

0 0 0 0

1 0 1 X

12

ab cd

00

01

00 01 11 10

11

10

•  Reduce the following to a POS form •  First find the essential prime implicates

Minimum product of sum: Ex 2

Page 13: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Min product of sums: Ex3

Given R(a,b,c,d) = Σm (3, 11, 12, 13, 14) D (a,b,c,d)= Σm (4, 8, 10)

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

13

ab cd 00 01 11 10

00

01

11

10

K-map

Page 14: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Min product of sums: Ex3

14 a

d

1 X 0 X

1 1 0 1

0 1 1 0

1 1 0 X

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

ab 00 01 11 10 cd

00

01

11

10

Given R(a,b,c,d) = Σm (3, 11, 12, 13, 14) D (a,b,c,d)= Σm (4, 8, 10)

Page 15: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Prime Implicates: ΠM (3,11), ΠM (12,13), ΠM(10,11), ΠM (4,12), ΠM (8,10,12,14) PI Q: Which of the following is a non-essential prime implicate? A.  ΠM(3,11) B.  ΠM(12,13) C.  ΠM(10,11) D.  ΠM(8,10,12,14)

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a

d

1 X 0 X

1 1 0 1

0 1 1 0

1 1 0 X

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

ab 00 01 11 10 cd

00

01

11

10

Page 16: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

16

0 2 6 4

1 3 7 5

X 0 1 0

1 0 0 X

ab c 00 01 11 10

0

1

-3-

(IV) (25pts) (Karnaugh Map) Use Karnaugh map to simplify functionf (a, b, c) = Σm(2, 3, 4, 7) +Σ d(0, 5). List all possible minimal sum of productsexpressions. Show the Boolean expressions. No need for the logic diagram.

(V) (25pts) (Karnaugh Map) Use Karnaugh map to simplify functionf (a, b, c) = Σm(1, 6) +Σ d(0, 5). List all possible minimal product of sums expres-sions. Show the Boolean expressions. No need for the logic diagram.

Page 17: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

17

0 2 6 4

1 3 7 5

X 0 1 0

1 0 0 X

ab c 00 01 11 10

0

1

Page 18: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Five variable K-map

0 4 12 8

c

d

b

e 1 5 13 9

3 7 15 11

2 6 14 10

16 20 28 24

c

d

b

e

a

17 21 29 25

19 23 31 27

18 22 30 26

Neighbors of m5 are: minterms 1, 4, 7, 13, and 21 Neighbors of m10 are: minterms 2, 8, 11, 14, and 26

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a=0 a=1

bc de

00 01 11 10 00 01 11 10

00

01 11 10

Page 19: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Reading a Five variable K-map

0 4 12 8

c

d

b

e 1 5 13 9

3 7 15 11

2 6 14 10

16 20 28 24

c

d

b

e

a

17 21 29 25

19 23 31 27

18 22 30 26

19

a=0 a=1

bc de

00 01 11 10 00 01 11 10

00

01 11 10

1  1 1 1 1

1 1 1 1 1

1 1

1 1 1 1 1 1

Page 20: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Six variable K-map d

e

c

f

d

e

c d

e

c

f

48 52 60 56

d

e

c b

49 53 61 57

51 55 63 59

50 54 62 58

a

32 36 44 40

33 37 45 41

35 39 47 43

34 38 46 42

f

f

0 4 12 8

1 5 13 9

3 7 15 11

2 6 14 10

16 20 28 24

17 21 29 25

19 23 31 27

18 22 30 26

20

bc de

ab=(0,0) ab=(0,1)

ab=(1,0) ab=(1,1)

Page 21: Lecture 8: K-Map to POS reductions K-maps in higher dimensions · Lecture 8: K-Map to POS reductions K-maps in higher dimensions CSE 140: Components and Design Techniques for Digital

Reading

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[Harris] Chapter 2, 2.7