Hi all, Does anyone here have any experience/tips for _convolutive_ NMF in scikit-learn (or in numpy more generally)? scikit-learn has NMF decomposition, hooray, but nothing for the convolutive version.
"Convolutive" here means that the bases are not just 1-dimensional but 2-dimensional: the basic NMF model X=WH is expanded so that each element of H is convolved with an element of W, not just multiplied. Useful for timeseries such as audio spectrograms: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.320.5545&rep=rep1&type=pdf http://eprints.maynoothuniversity.ie/1375/1/getPDF2.pdf Thanks Dan -- Dan Stowell EPSRC Research Fellow Centre for Digital Music Queen Mary, University of London Mile End Road, London E1 4NS http://www.mcld.co.uk/research/ ------------------------------------------------------------------------------ BPM Camp - Free Virtual Workshop May 6th at 10am PDT/1PM EDT Develop your own process in accordance with the BPMN 2 standard Learn Process modeling best practices with Bonita BPM through live exercises http://www.bonitasoft.com/be-part-of-it/events/bpm-camp-virtual- event?utm_ source=Sourceforge_BPM_Camp_5_6_15&utm_medium=email&utm_campaign=VA_SF _______________________________________________ Scikit-learn-general mailing list Scikit-learn-general@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
