[HN Gopher] Eigentechno - Applying Principal Component Analysis ... ___________________________________________________________________ Eigentechno - Applying Principal Component Analysis to electronic music loops Author : zorked Score : 18 points Date : 2020-10-18 20:22 UTC (2 hours ago) (HTM) web link (www.math.uci.edu) (TXT) w3m dump (www.math.uci.edu) | lgrebe wrote: | Neat. Waiting for "the drop" or changes in the music that "tickle | my senses" makes me wonder if an emergent Property (the | pleasurable sound from the composition of base, kick, Snares, | "woop" in this case) can be covered with PCA. | | More than the sum of its parts (emergent) is to be reduced to its | principal components. | Der_Einzige wrote: | Have you considered trying more sophisticated dimensionality | reduction algorithms? I'm especially interested in seeing the | results of UMAP on this dataset. | | Also, what about doing inverse transforms to try to hallucinate | music? | JorgeGT wrote: | One of the issues when using PCA (or POD, Karhunen-Loeve | expansion... whatever your field calls it) on a dataset is that | it optimizes the spectral content of each mode to obtain the best | possible orthonormal basis for the reconstruction, so you can get | very different frequencies in a single mode. Should you want to | restrict this, you could use DMD (Dynamic Mode Decomposition, one | frequency only per each mode) or mPOD (Multi-Scale Proper | Orthogonal Decomposition, a restricted set of frequencies per | mode). ___________________________________________________________________ (page generated 2020-10-18 23:00 UTC)