# What is the bipolar input and bipolar output truth table of ANDNOT function

• MHB
• shivajikobardan
In summary, a bipolar input and bipolar output truth table can be used to determine whether a given input is equal to a given output. The truth table defines the output as a function of the input, and the output can be either 0 or 1. The bipolar input and bipolar output truth table of the ANDNOT function is described in Wikipedia.
shivajikobardan

What is the bipolar input and bipolar output truth table of ANDNOT function
Could you remind the definitions of bipolar output truth table and ANDNOT function?

Evgeny.Makarov said:
Could you remind the definitions of bipolar output truth table and ANDNOT function?
I forgot to clarify, bipolar means 0-->-1 and 1------->1 that's it. My confusion is with truth table of AND NOT function. What is its truth table. I have made one above and written books' truth table as well. Could you please clarify that only?

shivajikobardan said:
I forgot to clarify, bipolar means 0-->-1 and 1------->1
I have not encountered Boolean algebra with negative values like $-1$ above. If minus is a typo and you meant 0 --> 1 and 1 --> 1, then did you mean a constant function of one argument that is always equal to 1? How is it related to AND NOT?

If by AND NOT you mean NAND, which maps $x$ and $y$ to $\overline{x\&y}$, then it is described in Wikipedia. It maps all pairs of arguments to 1 except (1, 1), which it maps to 0. If I misunderstood your question, please write it more clearly.

Evgeny.Makarov said:
I have not encountered Boolean algebra with negative values like $-1$ above. If minus is a typo and you meant 0 --> 1 and 1 --> 1, then did you mean a constant function of one argument that is always equal to 1? How is it related to AND NOT?

If by AND NOT you mean NAND, which maps $x$ and $y$ to $\overline{x\&y}$, then it is described in Wikipedia. It maps all pairs of arguments to 1 except (1, 1), which it maps to 0. If I misunderstood your question, please write it more clearly.

Glad you found the answer. Next time please write the complete problem statement and its context in the body of the first message and not only in the thread title. In this case it is essential that the question deals with neural networks.

Evgeny.Makarov said:
Glad you found the answer. Next time please write the complete problem statement and its context in the body of the first message and not only in the thread title. In this case it is essential that the question deals with neural networks.
Ok I will write everything in detail from now on. Thank for advice.

## 1. What is a bipolar input and bipolar output truth table?

A bipolar input and bipolar output truth table is a table that shows the possible combinations of inputs and their corresponding outputs for a logic function. "Bipolar" means that the inputs and outputs can take on two values: positive and negative.

## 2. What is the ANDNOT function?

The ANDNOT function is a logical operation that takes two inputs and produces an output based on the following truth table:
Input 1 Input 2 Output
0 0 0
0 1 1
1 0 0
1 1 0
In other words, if both inputs are 0 or if input 1 is 1 and input 2 is 1, the output is 0. If input 1 is 0 and input 2 is 1, the output is 1.

## 3. What does bipolar input and output mean in the context of logic functions?

In the context of logic functions, bipolar input and output means that the inputs and outputs can take on two values: positive and negative. This is represented by using 0 for negative and 1 for positive.

## 4. How is the truth table for the ANDNOT function different from other logic functions?

The truth table for the ANDNOT function is different from other logic functions because it produces a 0 output only when both inputs are 0 or when input 1 is 1 and input 2 is 1. In contrast, other logic functions may produce a 0 output for different combinations of inputs.

## 5. How is the bipolar input and output truth table of the ANDNOT function useful in scientific research?

The bipolar input and output truth table of the ANDNOT function is useful in scientific research because it can be used in digital circuits to perform logical operations. It is particularly useful in digital signal processing and can be used to design circuits for applications such as noise reduction and image processing.

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