4 ms·
I thought for this the standard practice is fixed-point. Requires more planning and mental gymnastics but usually much faster and gives you full control of the
by btashton 6y ago
I thought for this the standard practice is fixed-point. Requires more planning and mental gymnastics but usually much faster and gives you full control of the precision.
Maybe this has changed from my DSP days.
- krapht 6y agoI am confused. If you used to work in DSP then you know the standard practice involves MATLAB, where the default is double precision. This is also the default datatype in NumPy. Most engineers don't like working in fixed-point unless they have to for other reasons, like moving it onto an FPGA or something.
- mng2 6y agoThe person you're responding to probably worked with DSP chips, which are generally not floating-point. e.g. Motorola 56000, TigerSHARC, Blackfin.
- Keyframe 6y agoWhy not? Because of interop with other libs/tools? It's not _that_ hard, but I can see the problem if whole workflow isn't like that.
- l33tman 6y agoYou know a cool thing you can do to help fixed point interop between operations in a complex system where you absolutely don't want to accidentally overflow anywhere? You can tack on some bits to the number to control an overall scale of the fixed point number. Let's call it an exponent ;)
- Keyframe 6y agoAgreed. Let's standardize it :))
- btashton 6y agomost of it was FPGA work but in some cases DSP processors. Even when you have floating point support it is much slower than if you use fixed point. As for MATLAB, modeled plenty of filters in it for fixed-point math.