I have been doing some multimodal signal analysis, and sometimes ICA is used for detecting statistically independent components.
From my understanding, say if you have 2 sources and 2 receivers/sensors, you can have a unique solution, however if you have, say thousands of source, like in EEG, and 32 sensors, you need mathematically limiting tools to get to that approximate solution based on the context.
However, I kept wondering for example, if you are able to distinguish between 3 instruments in a song, from one track? so one sensor? Is there any research area to do with this? If yes, could you please direct me towards the right direction?
I am interested in statistical methods. I have already read a paper that used deep learning on music tracks that have the combined version and each instruments independent sounds, and ofc, uses them as input data, I am not interested in this.