Convert your problems from the time domain to the frequency domain using Fourier transforms, wavelets and many other transforms.
A time–frequency distribution function ideally has the following properties:
- High resolution in both time and frequency, to make it easier to be analyzed and interpreted.
- No cross-term to avoid confusing real components from artifacts or noise.
- A list of desirable mathematical properties to ensure such methods benefit real-life application.
- Lower computational complexity to ensure the time needed to represent and process a signal on a time–frequency plane allows real-time implementations.
The first property is high resolution (the problem under a magnifying lens), the second is to avoid confusion (the problem under natural light at noon or 100W warm light)
Third, a list of useful features (list what you want out of the problem-specs) and, finally, how to get it with minimal effort or cost? (list the ways to get it done and how much time or money to spend, choose the lowest-bill of materials, BOM)
When facing infinity, just calculate the limit, easy, peasy, algebreezy.