IQmath Library
16-Bit vs. 32-Bit
The "IQmath" approach could also be used on 16 bit sized numbers and for many problems, this
is sufficient resolution. However, in many control cases, the user needs to use many different
"Q" values to accommodate the limited resolution of a 16-bit number.
With DSP devices like the TMS320C28x processor, which can perform 16 bit and 32 bit sized
math with equal efficiency, the choice becomes more of productivity (time to market). Why
bother spending a whole lot of time trying to code using 16 bit numbers when you can simply use
32 bit numbers, pick one value of "Q" that will accommodate all cases and not worry about
spending too much time optimizing.
Of course there is a concern on data RAM usage if numbers that could be represented in 16 bits
all use 32 bits. This is becoming less of an issue in today's processors because of the finer tech-
nology used and the amount of RAM that can be cheaply integrated. However, in many cases,
this problem can be mitigated by performing intermediate calculations using 32 bit numbers and
converting the input from 16 bit to 32 bit and converting the output from 32 to 16 bit before stor-
ing the final results. In many problems, it is the intermediate calculations that require additional
accuracy to avoid quantization problems.
C28x - Numerical Concepts & IQmath 8 - 25
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