There is a chronic problem in audio/image processing where domain experts have developed their own notation and terminology and do a really poor job connecting it to the simple concepts they represent.
> Had he explained it in terms of pixels and loops instead of what was probably (for us) a Greek letter soup, I am sure we would have understood.
Unfortunately concretizing the math to realizations leaves you with a cookbook for implementing the least interesting bits of signal processing. Looking at some matrix multiplication as for loops doesn't teach you how a filter works.
Like just to give an example, I don't think it's possible to come up with an explanation of the Remez Exchange Algorithm in any physically meaningful context since it's fundamentally about recognizing the mathematical properties of a higher order abstraction of the system designed with it. But we can be a bit smarter about how we write, since "an iterative algorithm used to find simple approximations to functions, specifically, approximations by functions in a Chebyshev space that are the best in the uniform norm L∞ sense" is Wikipedia word soup that belies the concepts and connections that make it useful. It's just hard to do it in a sentence and not a semester.
> Had he explained it in terms of pixels and loops instead of what was probably (for us) a Greek letter soup, I am sure we would have understood.
Unfortunately concretizing the math to realizations leaves you with a cookbook for implementing the least interesting bits of signal processing. Looking at some matrix multiplication as for loops doesn't teach you how a filter works.
Like just to give an example, I don't think it's possible to come up with an explanation of the Remez Exchange Algorithm in any physically meaningful context since it's fundamentally about recognizing the mathematical properties of a higher order abstraction of the system designed with it. But we can be a bit smarter about how we write, since "an iterative algorithm used to find simple approximations to functions, specifically, approximations by functions in a Chebyshev space that are the best in the uniform norm L∞ sense" is Wikipedia word soup that belies the concepts and connections that make it useful. It's just hard to do it in a sentence and not a semester.