Is fixed-point more accurate?

Is fixed-point more accurate?

If you need higher resolution and do not need dynamic range, then use fixed-point. If you need dynamic range and do not need higher resolution, then used floating-point. If you need both, use more bits. Note that the fixed scale means fixed-point will sometimes be less accurate than floating-point.

Why fixed-point operation is usually used?

The advantage of using a fixed-point representation is performance and disadvantage is relatively limited range of values that they can represent. So, it is usually inadequate for numerical analysis as it does not allow enough numbers and accuracy.

What is the difference between fixed-point and floating-point?

Fixed point is a representation of real data type for a number that has a fixed number of digits after the radix point. Floating point is a formulaic representation of real numbers as an approximation so as to support a tradeoff between range and precision.

When to use full portion of Union in fixed point math?

When adding, subtracting, or performing logical comparisons on two variables with the same-resolution fixed-point numbers, use the .full portion of the union and perform straight integer arithmetic. Listing 3 shows a small routine that performs each operation and prints the result for the number of type FIXED1_7 .

When to use different resolution fixed point numbers?

When adding, subtracting, or performing logical comparisons on two variables with different-resolution fixed-point numbers, first scale the different resolution number to the same resolution as the result. Listing 4 shows a small routine that performs some mixed operations and prints the results.

How to convert a variable to a fixed point?

Substitute the actual value for the equations using X and Y in each of the following macros. Define a macro to convert a value into the fixed-point variable. A is the integer part and B is the decimal part, expressed as normal decimal.

When to use floating point or fixed point math?

Round this sum up to either 8, 16, or 32. This sum will be referred to later as the FULLSIZEINT. If this sum is greater than the maximum integer size in your system, then floating-point numbers are required and will probably be more efficient. The results for our example requirements for all the initial parameters are shown in Table 1.