Timeline for Room Impulse Response Domain of Sparsity
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Mar 30 at 13:31 | vote | accept | Con | ||
| Dec 28, 2023 at 2:06 | comment | added | Con | Another problem is, how can I handle the horrendous high dimensionality of the problem? If I want to apply some 'mainstream' techniques such as trying what sinc interpolation might yield, I need over 300GB of memory, considering the numbers I mentioned in my comment on my question. This also hinders any application of machine learning methods or any type of interpolation over the dimensions of the room. | |
| Dec 28, 2023 at 1:58 | comment | added | Con | The interesting part is, people are publishing research papers that employ optimization to solve the problem simply by assuming some sparsity. I am not sure what difference it makes if an impulse is applied (hence RIRs are recorded as direct responses to it), or a sound source is applied (hence the output is a response to that specific sound source) then deconvolution is used to get the impulse response out of that. Is it the case that by applying a normal (hearable) sound we can assume sparsity in frequency (which is not the case with impulses and impulse responses)? | |
| Dec 25, 2023 at 21:49 | history | answered | Hilmar | CC BY-SA 4.0 |