Results 121 to 130 of about 1,313 (162)
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A simple variable step algorithm for blind source separation (BSS)
Neural Networks for Signal Processing VIII. Proceedings of the 1998 IEEE Signal Processing Society Workshop (Cat. No.98TH8378), 2002Most of the existing online learning algorithms for blind source separation are confronted with the learning step-size problem. In this paper, we propose a way to decompose the demixing matrix into row vector space. From the row vector viewpoint, a variable step (VS) algorithm for the blind source separation problem is proposed.
M.O. Pun, Y. Hirai
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Separation of twins fetal ECG by means of blind source separation (BSS)
21st IEEE Convention of the Electrical and Electronic Engineers in Israel. Proceedings (Cat. No.00EX377), 2002The maternal ECG (MECG) is the main source of interference in fetal ECG (FECG) monitoring. The MECG is detected at all electrodes placed on the mother's skin (thoracic and abdominal). In the case of multi-fetal pregnancies the traditional adaptive filtering technique provides a "maternal clean" signal consisting of the two fetal ECG signals.
A. Kam, A. Cohen
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International Journal of Neural Systems, 2004
In this paper, we review recent advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixing models. After a general introduction to BSS and ICA, we discuss in more detail uniqueness and separability issues, presenting some new results.
Christian, Jutten, Juha, Karhunen
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In this paper, we review recent advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixing models. After a general introduction to BSS and ICA, we discuss in more detail uniqueness and separability issues, presenting some new results.
Christian, Jutten, Juha, Karhunen
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EEG filtering based on blind source separation (BSS) for early detection of Alzheimer's disease
Clinical Neurophysiology, 2005Development of an EEG preprocessing technique for improvement of detection of Alzheimer's disease (AD). The technique is based on filtering of EEG data using blind source separation (BSS) and projection of components which are possibly sensitive to cortical neuronal impairment found in early stages of AD.Artifact-free 20s intervals of raw resting EEG ...
Andrzej, Cichocki +5 more
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2014 IEEE 7th International Workshop on Computational Intelligence and Applications (IWCIA), 2014
This paper presents a study of Blind Source Separation (BSS) application in telemedicine problem, especially during medical data recording. There are two techniques that will be investigated, Natural Gradient Method (NGM) and Fast Independent Coeffient Analysis(FastICA) with main source signals are Electrocardiograph (ECG), Electroencephalograph (EEG),
Alvin Sahroni +2 more
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This paper presents a study of Blind Source Separation (BSS) application in telemedicine problem, especially during medical data recording. There are two techniques that will be investigated, Natural Gradient Method (NGM) and Fast Independent Coeffient Analysis(FastICA) with main source signals are Electrocardiograph (ECG), Electroencephalograph (EEG),
Alvin Sahroni +2 more
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‘Shadow BSS’ for Blind Source Separation in Rapidly Time-Varying Acoustic Scenes
2007This paper addresses the tracking capability of blind source separation algorithms for rapidly time-varying sensor or source positions. Based on a known algorithm for blind source separation, which also allows for simultaneous localization of multiple active sources in reverberant environments, the source separation performance will be investigated for
S. Wehr +3 more
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2017 IEEE 2nd International Conference on Big Data Analysis (ICBDA)(, 2017
An improved canonical correlation analysis (CCA) approach for multi-subject blind source separation (BSS) of brain functional magnetic resonance imaging (fMRI) data is proposed. Group-level comparison analysis has attracted increasing interest in the human brain fMRI analysis.
Xing-Jie Wu +5 more
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An improved canonical correlation analysis (CCA) approach for multi-subject blind source separation (BSS) of brain functional magnetic resonance imaging (fMRI) data is proposed. Group-level comparison analysis has attracted increasing interest in the human brain fMRI analysis.
Xing-Jie Wu +5 more
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Interspeech 2004, 2004
A number of real-life speech applications using BSS have been reported for two channel applications but only a few have been reported for multi-channel (more than 2 channels) applications. Moreover these mostly involve simulation studies or real-life separations in controlled settings.
Erik Visser +3 more
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A number of real-life speech applications using BSS have been reported for two channel applications but only a few have been reported for multi-channel (more than 2 channels) applications. Moreover these mostly involve simulation studies or real-life separations in controlled settings.
Erik Visser +3 more
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IET 3rd International Conference MEDSIP 2006. Advances in Medical, Signal and Information Processing, 2006
A method of signal recovery of the pattern electroretinogram (PERG) from recordings contaminated with electrical artefacts resulting from eye movements and blinks is described. The single channel data are decomposed into statistically-independent components using the jadeR ICA algorithm preceded by a dynamical embedding matrix with dimensions dictated ...
A.C. Fisher +4 more
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A method of signal recovery of the pattern electroretinogram (PERG) from recordings contaminated with electrical artefacts resulting from eye movements and blinks is described. The single channel data are decomposed into statistically-independent components using the jadeR ICA algorithm preceded by a dynamical embedding matrix with dimensions dictated ...
A.C. Fisher +4 more
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2007 6th International Conference on Information, Communications & Signal Processing, 2007
Eight out of one thousand born live infants have some form of heart defect, making it the single most common class of congenital abnormalities. Identification of these cases during early pregnancy reduces risks by timely treatment or planned delivery.
Abhinav Gupta +3 more
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Eight out of one thousand born live infants have some form of heart defect, making it the single most common class of congenital abnormalities. Identification of these cases during early pregnancy reduces risks by timely treatment or planned delivery.
Abhinav Gupta +3 more
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