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The algorithm for NMF denoising goes as follows. Two dictionaries, one for speech and one for noise, need to be trained offline. Once a noisy speech is given, we first calculate the magnitude of the Short-Time-Fourier-Transform. Second, separate it into two parts via NMF, one can be sparsely represented by the speech dictionary, and the other part can be sparsely represented by the noise dictionary. Third, the part that is represented by the speech dictionary will be the estimated clean speech.
=== Population
Sparse NMF is used in [[Population genetics]] for estimating individual admixture coefficients, detecting genetic clusters of individuals in a population sample or evaluating [[genetic admixture]] in sampled genomes. In human genetic clustering, NMF algorithms provide estimates similar to those of the computer program STRUCTURE, but the algorithms are more efficient computationally and allow analysis of large population genomic data sets.<ref>{{Cite journal
| vauthors = Frichot E, Mathieu F, Trouillon T, Bouchard G, Francois O
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