Can KMAP Fully Minimize This SOP Expression?

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In summary: This was a great explanation and makes total sense. Thanks again!In summary, by using a Karnaugh map, the expression for the Boolean function f was initially found to be !y_{1}!y_{0} + !x_{1}x_{0}!y_{1} + x_{1}!y_{1} + x_{1}!y_{0} + x_{1}x_{0}y_{1}. However, the expression can be further minimized by removing overlapping variables, resulting in the simplest sum of product expression for f: f = x_{1}x_{0} + !y_{1}!y_{0} + x_{1}!y_{0} +
  • #1
shamieh
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0
I used a KMAP and got this as my expression

[tex]f = !y_{1}!y_{0} + !x_{1}x_{0}!y_{1} + x_{1}!y_{1} + x_{1}!y_{0} + x_{1}x_{0}y_{1}[/tex]Is there any way I can minimize this? Maybe I'm just not seeing it. I thought the whole point of a KMAP was to minimize the expression?

Some how the answer is this: [tex] f = x_{1}x_{0} + !y_{1}!y_{0} + x_{1}!y_{0} + x_{0}!y_{1} + x_{1}!y_{1}[/tex]

If anyone is interested I had to design a circuit with output f with 4 inputs. I'm supposed to be showing the simplest sum of product expression for f. My f row for my truth table was this:
1
0
0
0

1
1
0
0

1
1
1
0

1
1
1
1Thanks in advance
 
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  • #2
shamieh said:
I used a KMAP and got this as my expression

[tex]f = !y_{1}!y_{0} + !x_{1}x_{0}!y_{1} + x_{1}!y_{1} + x_{1}!y_{0} + x_{1}x_{0}y_{1}[/tex]

...

Some how the answer is this: [tex] f = x_{1}x_{0} + !y_{1}!y_{0} + x_{1}!y_{0} + x_{0}!y_{1} + x_{1}!y_{1}[/tex]
You can turn the three-variable minterms into two-variable ones, namely, remove $!x_1$ from $x_0!x_1!y_1$ and $y_1$ from $x_0x_1y_1$.
 
  • #3
Evgeny.Makarov said:
You can turn the three-variable minterms into two-variable ones, namely, remove $!x_1$ from $x_0!x_1!y_1$ and $y_1$ from $x_0x_1y_1$.
Well I can't combine them because they don't differ by two variables correct? So what minimization "tool" should I use? Should I factor something? I mean how do you just "get rid of them". See what I'm saying? What method I should I be using? Sorry if I sound ignorant.
 
  • #4
When you remove a variable from a three-variable minterm, its representation in the Karnaugh map grows from 2 to 4 cells. However, if the added two cells are already covered by other minterms, then the Boolean function does not change.

In this case, the minterm $x_0y_1y_1$ represents two cells in the middle of column 3 ($x_0=x_1=1$). When you remove $y_1$, the result is the complete column 3. But the top cell of column 3 is already covered by $!y_0!y_1$, and the bottom cell of column 3 is covered by $x_1!y_1$. So removing $y_1$ from $x_0y_1y_1$ does not change the function. A similar thing happens with turning $x_0!x_1!y_1$ into $x_0!y_1$.

When reading off a minimal formula from a Karnaugh map, the temptation is always to break the cells corresponding to 1 into disjoint regions. But this results in smaller regions and therefore larger minterms. Instead, one must make regions as large as possible by using the fact that overlap is allowed.
 
  • #5
Awesome explanation! Thanks so much. So it looks like I probably missed a overlapping grouping I could of put together then - thus getting not exactly the complete minimization.
 

FAQ: Can KMAP Fully Minimize This SOP Expression?

What is SOP in KMAP and why is it important to minimize it?

The Sum of Products (SOP) is a logical expression used to represent Boolean functions in a simplified form. It is important to minimize SOP because it reduces the complexity of the function, making it easier to design and implement in digital logic circuits.

What is a KMAP and how does it help in minimizing SOP?

KMAP (Karnaugh Map) is a graphical method used to simplify Boolean expressions. It is a visual representation of truth table values and helps identify patterns and reduce the number of terms in an SOP expression, thus minimizing it.

What are the steps involved in minimizing SOP using KMAP?

The steps involved in minimizing SOP using KMAP are:

  • 1. Identify the minterms and their corresponding values from the truth table.
  • 2. Group the adjacent minterms that have a value of 1 in the KMAP.
  • 3. Simplify the grouped terms by eliminating redundant variables.
  • 4. Write the simplified expression in SOP form.

Are there any limitations to using KMAP for minimizing SOP?

Yes, there are some limitations to using KMAP for minimizing SOP. It is only applicable for functions with up to 6 variables. Also, it can become complex and time-consuming for larger truth tables.

Can we use KMAP to minimize SOP for functions with don't care conditions?

Yes, KMAP can also be used to minimize SOP for functions with don't care conditions. These conditions are represented by 'X' in the KMAP and can be treated as either 0 or 1 depending on which value results in a simpler expression.

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