0
$\begingroup$

I am testing my supervised NMF algorithm to extract signal from observation that have only one source inside. I am new here and I wonder this is very weak model or not? Is it acceptable in signal processing academic paper to start experimental result with factorization of only one source separation from the environment?

$\endgroup$
4
  • 1
    $\begingroup$ I'd say that this is a very good starting point since there is nothing simpler that makes sense. By doing so you will already tackle enough problems. $\endgroup$
    – jojeck
    Nov 1, 2017 at 11:25
  • $\begingroup$ @jojek thanks so much. Just want to ask that do you know some papers doing source separation on one source? May you please introduce them? $\endgroup$
    – Jan
    Nov 1, 2017 at 11:31
  • 1
    $\begingroup$ Have you seen these two? 1, 2. Then it's just a matter of tracking the references $\endgroup$
    – jojeck
    Nov 1, 2017 at 11:38
  • 1
    $\begingroup$ You can also have a look at a recent answer, it might help you somehow. $\endgroup$
    – jojeck
    Mar 27, 2018 at 10:24

1 Answer 1

0
$\begingroup$

Yes, that's a first sanity check. Basically, the idea of averaging multiple observations of a single signal buried in noise is a basic issue in signal processing. You can have several observations with multiple noise realizations and statistics, with different delays on the signal, with different data transformations (more or less linear).

If this does not work in your case, don't expect to much of NMF performance on multiple sources, and verify assumptions or test other source separation methods.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Not the answer you're looking for? Browse other questions tagged or ask your own question.