On Nonnegative Matrix Factorization Algorithms for Signal-Dependent Noise with Application to Electromyography Data
Nonnegative matrix factorization (NMF) by the multiplicative updates algorithm is a powerful machine learning method for decomposing a high-dimensional nonnegative matrix V into two nonnegative matrices, W and H, where V ~ WH. It has been successfully applied in the analysis and interpretation of la...
| Main Authors: | , |
|---|---|
| Other Authors: | |
| Format: | Article |
| Language: | en_US |
| Published: |
MIT Press
2015
|
| Online Access: | http://hdl.handle.net/1721.1/96302 |