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An Independent Component Analysis (ICA) Based Approach for EEG Person Authentication
2009 3rd International Conference on Bioinformatics and Biomedical Engineering, 2009Exploring brain electrical activity represented by electroencephalogram (EEG) signals for biometric applications has recently attracted increasing research attention since EEG pattern has been shown to be unique for each individual. In this paper, we propose an Independent Component Analysis (ICA) based EEG feature extraction and modeling approach for ...
Chen He, Jane Wang
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Analysis on Saccade-Related Independent Components by Various ICA Algorithms for Developing BCI
2009Saccade-related electroencephalogram (EEG) signals have been the subject of application oriented research by our group toward developing a brain computer interface (BCI). Our goal is to develop novel BCI based on eye movements system employing EEG signals on-line.
Arao Funase +4 more
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Application of independent component analysis (ICA) method to the Raman spectra processing
SPIE Proceedings, 2005Independent component analysis (ICA) method was applied as a processing step for Raman spectra. 136 Raman spectra were acquired from urine samples from 18 subjects. Each spectrum was acquired from different sample. 785nm, 100mW (at sample) laser with 2048 element linear silicon TE cooled CCD were used.
So Hyun Chung +2 more
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Face Recognition Using Independent Component Analysis of GaborJet (GaborJet-ICA)
2010 6th International Colloquium on Signal Processing & its Applications, 2010In this paper a new face recognition technique based on Independent Component Analysis of GaborJet (GaborJet-ICA) is proposed. Existing face recognition systems using Gabor wavelets convolve a whole face image with a set of 40 Gabor wavelets. We have derived Gabor feature vector from facial landmarks (fiducial points) known as GaborJets.
S G Bhirud
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An overview of ICA (independent component analysis) applications in remote sensed data
SPIE Proceedings, 2005ICA has been a well studied subject in recent years. Its implementation may employ neural networks or adaptive learning techniques. In contrast to PCA, the objective of ICA is to extract components with high-order statistical independence. The concept and process of deriving the independent components have had motivated the development of many ...
C. H. Chen, Zhenhai Wang
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Industrial & Engineering Chemistry Research, 2007
Many of the current multivariate statistical process monitoring techniques (such as principal component analysis (PCA) or partial least squares (PLS)) do not utilize the non-Gaussian information of...
Zhiqiang Ge, Zhihuan Song
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Many of the current multivariate statistical process monitoring techniques (such as principal component analysis (PCA) or partial least squares (PLS)) do not utilize the non-Gaussian information of...
Zhiqiang Ge, Zhihuan Song
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Independent components analysis with the JADE algorithm – Why ICA"
2014absent
Rutledge, Douglas +1 more
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Classifying hemodynamics of MR brain perfusion images using independent component analysis (ICA)
Proceedings of the International Joint Conference on Neural Networks, 2003., 2004Dynamic-susceptibility-contrast MR imaging is a widely used perfusion imaging technique that records signal changes on images caused by the passage of contrast-agent particles in the human brain after a bolus injection of contrast agent. The signal changes over time on different brain tissues represent distinct blood supply patterns and are crucial for
Yu-Te Wu +5 more
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Real- Time EEG Data Processing Using Independent Component Analysis (ICA)
2022 14th International Conference on Communications (COMM), 2022Leontin Tuta +3 more
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