Non-Negative Blind Source Separation Algorithm Based on Minimum Aperture Simplicial Cone
暂无分享,去创建一个
Christian Jutten | Antoine Souloumiac | Meriem Jaïdane | Wendyam Serge Boris Ouedraogo | C. Jutten | A. Souloumiac | Mériem Jaïdane | W. Ouedraogo
[1] Régis Huez,et al. Application of Non-negative Matrix Factorization to fluorescence spectroscopy , 2004, 2004 12th European Signal Processing Conference.
[2] Chong-Yung Chi,et al. A Convex Analysis-Based Minimum-Volume Enclosing Simplex Algorithm for Hyperspectral Unmixing , 2009, IEEE Transactions on Signal Processing.
[3] H. Sebastian Seung,et al. Learning the parts of objects by non-negative matrix factorization , 1999, Nature.
[4] Yue Wang,et al. Gene expression dissection by non-negative well-grounded source separation , 2008, 2008 IEEE Workshop on Machine Learning for Signal Processing.
[5] Elmar Wolfgang Lang,et al. Towards unique solutions of non-negative matrix factorization problems by a determinant criterion , 2011, Digit. Signal Process..
[6] David Brie,et al. Non-negative source separation: range of admissible solutions and conditions for the uniqueness of the solution , 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..
[7] Xiang Fang,et al. Feature Extraction Approach for Mass Spectrometry Imaging Data Using Non-negative Matrix Factorization , 2012 .
[8] D. Brie,et al. Separation of Non-Negative Mixture of Non-Negative Sources Using a Bayesian Approach and MCMC Sampling , 2006, IEEE Transactions on Signal Processing.
[9] Hairong Qi,et al. Endmember Extraction From Highly Mixed Data Using Minimum Volume Constrained Nonnegative Matrix Factorization , 2007, IEEE Transactions on Geoscience and Remote Sensing.
[10] Chong-Yung Chi,et al. A Convex Analysis Framework for Blind Separation of Non-Negative Sources , 2008, IEEE Transactions on Signal Processing.
[11] Tuomas Virtanen,et al. Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria , 2007, IEEE Transactions on Audio, Speech, and Language Processing.
[12] Ali Mohammad-Djafari,et al. Bayesian Blind Source Separation of Positive Non Stationary Sources , 2004 .
[13] R. E. Cline,et al. The generalized inverse of a nonnegative matrix , 1972 .
[14] Mark D. Plumbley. Geometrical methods for non-negative ICA: Manifolds, Lie groups and toral subalgebras , 2005, Neurocomputing.
[15] P. Paatero,et al. Positive matrix factorization: A non-negative factor model with optimal utilization of error estimates of data values† , 1994 .
[16] José M. Bioucas-Dias,et al. Vertex component analysis: a fast algorithm to unmix hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[17] R. Hustinx,et al. Oncological applications of positron emission tomography with fluorine-18 fluorodeoxyglucose , 1996, European Journal of Nuclear Medicine.
[18] Mark D. Plumbley. Optimization Using Fourier Expansion over a Geodesic for Non-negative ICA , 2004, ICA.
[19] Victoria Stodden,et al. When Does Non-Negative Matrix Factorization Give a Correct Decomposition into Parts? , 2003, NIPS.
[20] Christian Jutten,et al. A Geometric Approach for Separating Several Speech Signals , 2004, ICA.
[21] Mark D. Plumbley,et al. Non-negative mixtures , 2010 .
[22] Mark D. Plumbley. Algorithms for nonnegative independent component analysis , 2003, IEEE Trans. Neural Networks.
[23] Mark D. Plumbley. Conditions for nonnegative independent component analysis , 2002, IEEE Signal Processing Letters.
[24] A. Cichocki,et al. Nonnegative Matrix Factorization with Temporal Smoothness and / or Spatial Decorrelation Constraints , 2005 .
[25] Jean-Philippe Thiran,et al. Sparse non-negative decomposition of speech power spectra for formant tracking , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[26] Lucas C. Parra,et al. Nonnegative matrix factorization for rapid recovery of constituent spectra in magnetic resonance chemical shift imaging of the brain , 2004, IEEE Transactions on Medical Imaging.
[27] Patrik O. Hoyer,et al. Non-negative Matrix Factorization with Sparseness Constraints , 2004, J. Mach. Learn. Res..
[28] José M. Bioucas-Dias,et al. Minimum Volume Simplex Analysis: A Fast Algorithm to Unmix Hyperspectral Data , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.
[29] Noboru Arimizu,et al. FDG-PET for the evaluation of tumor viability after anticancer therapy , 1994, Annals of nuclear medicine.
[30] Frank Klawonn,et al. MS-specific noise model reveals the potential of iTRAQ in quantitative proteomics , 2009, Bioinform..
[31] M. Guillaume,et al. Robust hyperspectral data unmixing with spatial and spectral regularized NMF , 2010, 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.
[32] José M. Bioucas-Dias,et al. A variable splitting augmented Lagrangian approach to linear spectral unmixing , 2009, 2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing.
[33] Nicolas Gillis,et al. Sparse and unique nonnegative matrix factorization through data preprocessing , 2012, J. Mach. Learn. Res..
[34] Hairong Qi,et al. A Constrained Non-Negative Matrix Factorization Approach to Unmix Highly Mixed Hyperspectral Data , 2007, 2007 IEEE International Conference on Image Processing.
[35] Karl Mechtler,et al. General statistical modeling of data from protein relative expression isobaric tags. , 2011, Journal of proteome research.
[36] Chong-Yung Chi,et al. Nonnegative Least-Correlated Component Analysis for Separation of Dependent Sources by Volume Maximization , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[37] Maurice D. Craig,et al. Minimum-volume transforms for remotely sensed data , 1994, IEEE Trans. Geosci. Remote. Sens..
[38] Yi Su,et al. Noninvasive Estimation of the Arterial Input Function in Positron Emission Tomography Imaging of Cerebral Blood Flow , 2013, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.
[39] Andrzej Cichocki,et al. Nonnegative Matrix and Tensor Factorization T , 2007 .
[40] Daniel D. Lee,et al. APPLICATION OF NON-NEGATIVE MATRIX FACTORIZATION TO DYNAMIC POSITRON EMISSION TOMOGRAPHY , 2001 .
[41] Andrzej Cichocki,et al. APPLICATIONS TO EXPLORATORY MULTI-WAY DATA ANALYSIS AND BLIND SOURCE SEPARATION , 2013 .
[42] A A Lammertsma. Noninvasive estimation of cerebral blood flow. , 1994, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.
[43] H. Sebastian Seung,et al. Algorithms for Non-negative Matrix Factorization , 2000, NIPS.
[44] Xueguang Shao,et al. Extraction of chemical information from complex analytical signals by a non-negative independent component analysis. , 2009, The Analyst.
[45] Andrzej Cichocki,et al. A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.
[46] H. Ressom,et al. LC-MS-based metabolomics. , 2012, Molecular bioSystems.
[47] Mark D. Plumbley,et al. Theorems on Positive Data: On the Uniqueness of NMF , 2008, Comput. Intell. Neurosci..
[48] Ann Nowé,et al. A New Geometrical BSS Approach for Non Negative Sources , 2010, LVA/ICA.