These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
118 related articles for article (PubMed ID: 34496387)
1. On the Achievability of Blind Source Separation for High-Dimensional Nonlinear Source Mixtures. Isomura T; Toyoizumi T Neural Comput; 2021 May; 33(6):1433-1468. PubMed ID: 34496387 [TBL] [Abstract][Full Text] [Related]
2. Advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures. Jutten C; Karhunen J Int J Neural Syst; 2004 Oct; 14(5):267-92. PubMed ID: 15593377 [TBL] [Abstract][Full Text] [Related]
3. Error-Gated Hebbian Rule: A Local Learning Rule for Principal and Independent Component Analysis. Isomura T; Toyoizumi T Sci Rep; 2018 Jan; 8(1):1835. PubMed ID: 29382868 [TBL] [Abstract][Full Text] [Related]
5. Stochastic ICA contrast maximisation using OJA's nonlinear PCA algorithm. Girolami M; Fyfe C Int J Neural Syst; 1997; 8(5-6):661-78. PubMed ID: 10065842 [TBL] [Abstract][Full Text] [Related]
6. Markov and Semi-Markov switching of source appearances for nonstationary independent component analysis. Hirayama J; Maeda S; Ishii S IEEE Trans Neural Netw; 2007 Sep; 18(5):1326-42. PubMed ID: 18220183 [TBL] [Abstract][Full Text] [Related]
7. A class of neural networks for independent component analysis. Karhunen J; Oja E; Wang L; Vigario R; Joutsensalo J IEEE Trans Neural Netw; 1997; 8(3):486-504. PubMed ID: 18255654 [TBL] [Abstract][Full Text] [Related]
8. Dimensionality reduction of fMRI time series data using locally linear embedding. Mannfolk P; Wirestam R; Nilsson M; Ståhlberg F; Olsrud J MAGMA; 2010 Dec; 23(5-6):327-38. PubMed ID: 20229085 [TBL] [Abstract][Full Text] [Related]
10. An algorithm for separation of mixed sparse and Gaussian sources. Akkalkotkar A; Brown KS PLoS One; 2017; 12(4):e0175775. PubMed ID: 28414814 [TBL] [Abstract][Full Text] [Related]
11. Stepwise model order estimation in blind source separation applied to ictal EEG. Hesse CW; James CJ Conf Proc IEEE Eng Med Biol Soc; 2004; 2004():986-9. PubMed ID: 17271846 [TBL] [Abstract][Full Text] [Related]
12. A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons. Heidarieh SM; Jahed M; Ghazizadeh A Neural Comput; 2019 Sep; 31(9):1853-1873. PubMed ID: 31335293 [TBL] [Abstract][Full Text] [Related]
13. Single channel blind source separation based local mean decomposition for biomedical applications. Guo Y; Naik GR; Nguyen H Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():6812-5. PubMed ID: 24111308 [TBL] [Abstract][Full Text] [Related]
14. Least-squares methods for blind source separation based on nonlinear PCA. Pajunen P; Karhunen J Int J Neural Syst; 1997; 8(5-6):601-12. PubMed ID: 10065838 [TBL] [Abstract][Full Text] [Related]
19. Principal component analysis can decrease neural networks performance for incipient falls detection: A preliminary study with hands and feet accelerations. Artoni F; Martelli D; Monaco V; Micera S Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():6194-6197. PubMed ID: 28269666 [TBL] [Abstract][Full Text] [Related]
20. A spectral clustering approach to underdetermined postnonlinear blind source separation of sparse sources. Van Vaerenbergh S; SantamarÃa I IEEE Trans Neural Netw; 2006 May; 17(3):811-4. PubMed ID: 16722185 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]