The floating point format is an objectively difficult format to visualize. It's probably due to the way it's represented in binary that makes it unintuitive. But mostly because we rarely tend to think about formats where the precision vary over a range of numbers. In this video, we'll peal back the layers and discover why floating point format is fundamentally different from fixed point format - its variable precision, and we'll explore a few ways of building an intuition for floating point numbers.
Watch the full playlist here:
• Audio Number Formats
Content:
0:00 Difficulty
2:15 Precision and accuracy
5:26 Visualizing precision
8:02 Ruler example
References:
https://fabiensanglard.net/floating_p...
https://docs.oracle.com/cd/E19957-01/...
/ floating-point-numbers-for-people-who-dont...
https://floating-point-gui.de/
This series describes the 2 fundamental formats for expressing numbers and audio data in the digital domain - fixed point format and floating point format. They both have their advantages, their areas of usage where they absolutely shine, and they both fall short or completely fail in other aspects. There is no one over the other. As audio and DSP enthusiasts, you'd need to know what where a particular format is preferred and under what circumstances they fall short. Why do digital playback hardware prefer fixed point number format. Why do DAW softwares prefer to work with floating point numbers? What even is a double precision number? And what number format do you use when implementing a DSP algorithm. The series will address these questions and a lot more.
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