Publisher
Springer Berlin Heidelberg
Reference15 articles.
1. Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature 401, 788–791 (1999)
2. Sajda, P., Du, S., Brown, T., Parra, L., Stoyanova, R.: Recovery of constituent spectra in 3D chemical shift imaging using nonnegative matrix factorization. In: 4th International Symposium on Independent Component Analysis and Blind Signal Separation, Nara, Japan, pp. 71–76 (2003)
3. Li, H., Adali, T., Wang, W., Emge, D., Cichocki, A.: Non-negative matrix factorization with orthogonality constraints and its application to Raman spectroscopy. The Journal of VLSI Signal Processing 48(1-2), 83–97 (2007)
4. Miron, S., Dossot, M., Carteret, C., Margueron, S., Brie, D.: Joint processing of the parallel and crossed polarized Raman spectra and uniqueness in blind nonnegative source separation. Chemometrics and Intelligent Laboratory Systems 105(1), 7–18 (2011)
5. Jia, S., Qian, Y.: Constrained nonnegative matrix factorization for hyperspectral unmixing. IEEE Transactions on Geoscience and Remote Sensing 47(1), 161–173 (2009)
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. GNMF with Newton-Based Methods;Artificial Neural Networks and Machine Learning – ICANN 2013;2013