Here is how an Short Term Fourier Transform works
You break your time series up in multiple segments. Each segment is nperseg samples long.
The segments overlap by noverlap samples. Your time resolution then is nperseg - noverlap , i.e. that is the time distance between neighboring segments. It's often called the "hop size"
You multiply the ...
This is subject of ridge analysis. The "quality" of a representation can be quantified as follows:
Ability to separate intrinsic modes / independent time-frequency components. This depends on
Time-frequency atom used; for wavelets, additionally on the scale-to-frequency mapping.
Frequency tiling scaling (linear/log): STFT (...
There is a fundamental tradeoff between frequency resolution and time resolution. The more granular you want your measurements in time, the less frequency distinction there is in each time bin. Conversely, longer time bins allow for very precise frequency distinctions. Higher sample rates will benefit your resolution in either dimension, but there will ...