Dear Marco thanks for your feedback. The dimensionality reduction algorithms are not externals...simply abstraction, so, I guess you will not find any trouble running it on Linux. If you run it on pd-extended, I'm pretty sure you will not need other any external libraries, with the exception of gridflow for the computation of eigenvectors in PCA.
Look into earGramv0.18>dependencies>abs you will find all abstractions here, or just open the file _absOverview. There's a couple of solutions for dimensionality reduction more or less complex such as: self-organised maps (SOM) PCA haar dct random projection star centroid and star coordinates (the only applied in earGram, actually) best, Gilberto 2013/11/6 Marco Donnarumma <[email protected]> > Hi Gilberto, > > thanks for sharing your work! > > I'm interested in looking at your dimensionality reduction objects, but > I'm a Linux user. Any plan to port your work to Linux? > > thanks! > best wishes, > M > > -- > Marco Donnarumma > New Media + Sonic Arts Practitioner, Performer, Teacher, Director. > Embodied Audio-Visual Interaction Research Team. > Department of Computing, Goldsmiths University of London > ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > Portfolio: http://marcodonnarumma.com > Research: http://res.marcodonnarumma.com > Director: http://www.liveperformersmeeting.net > > > On Sat, Oct 26, 2013 at 1:56 PM, Gilberto Bernardes > <[email protected]>wrote: > >> Hi, >> >> I’m working on a project for my PhD that recombines audio segments according >> to pre-defined generative methods. For those familiarised with concatenative >> sound synthesis, earGram reformulates the notion of unit selection >> algorithms to encompass generative music strategies. It relies heavily on >> timbreID a known library for PD by William Brent. >> >> >> So, here's the website that hosts the project: >> >> https://sites.google.com/site/eargram/ >> >> You can find project examples in the download section as well. P >> >> >> In addition there are plenty of abstractions that may interest you, in >> particular clustering and dimensionality reduction algorithms... >> >> As you can guess, I would like to get feedbacks and advises. >> >> >> Best, >> >> Gilberto Bernardes >> >> >> _______________________________________________ >> Pd-announce mailing list >> [email protected] >> http://lists.puredata.info/listinfo/pd-announce >> >> >
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