Structured sampling refers to the use of a combination of sampling and model-based methods. Instead of sampling the acoustic pressure wave, as in any typical audio recording, we sample more fundamental physical quantities such as an impulse response [#!JOSFP!#] that can be used to provide the desired level of both audio quality and model flexibility.
For example, in ``commuted waveguide synthesis'' (§8.7), the body resonator of a stringed instrument is efficiently modeled by its impulse response.
Another example is measuring the frequency response of a vibrating string so that a digital filter can be fit to that instead of being designed from first principles.
An advantage of sampling more fundamental characteristic signals such as impulse-responses is that they are often largely invariant with respect to controller state. This yields a far smaller memory footprint relative to brute force sampling of the acoustic pressure wave as a function of controller state.
There is an approximate continuum between sampling and physical modeling. That is, there is a wide range of possible hybrids between computational physical modeling and interpolation/manipulation of recorded samples. More computing power generally enables more accurate modeling and less memory usage.