Results 161 to 170 of about 5,521,232 (198)

Advances in Blind Source Separation (BSS) and Independent Component Analysis (ICA) for Nonlinear Mixtures.

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
exaly   +3 more sources

EEG Filtering Based on Blind Source Separation (BSS) for Early Detection of Alzheimer's Disease

Clinical Neurophysiology, 2005
Development 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 ...
Zbigniew Leonowicz, Sergei L Shishkin, Andrzej Cichocki   +2 more
exaly   +3 more sources

Blind Source Separation and Beamforming: Algebraic Technique Analysis

IEEE Transactions on Aerospace and Electronic Systems, 2004
Blind source separation (BSS) and blind beamforming schemes attempt to separate additive source signals, collected at a sensor array, and their direction-of-arrival (DOA).
L H Sibul
exaly   +2 more sources

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), 2002
The 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
openaire   +1 more source

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), 2002
Most 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
openaire   +1 more source

Performance of Blind Source Separation (BSS) Techniques for Mixed Source Signals of EEG, ECG, and Voice Signal

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),
Hendra Setiawan, Alvin Sahroni
exaly   +2 more sources

‘Shadow BSS’ for Blind Source Separation in Rapidly Time-Varying Acoustic Scenes

2007
This 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
Stefan Wehr, Anthony Lombard, Herbert Buchner, Walter Kellermann   +3 more
openaire   +2 more sources

A comparison of simultaneous 3-channel blind source separation to selective separation on channel pairs using 2-channel BSS

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 M. Visser, Kwokleung Chan, Stanley Kim, Te-Won Lee   +3 more
openaire   +1 more source

EMD-BSS: A Hybrid Methodology Combining Empirical Mode Decomposition and Blind Source Separation to Eliminate the Ocular Artifacts From EEG Recordings

Biomedical Signal Processing and Control
Manousos A. Klados, Benayad Nsiri, Christos Stergiadis   +2 more
exaly   +3 more sources

An Improved Group BSS-CCA Method for Blind Source Separation of Functional MRI Scans of the Human Brain

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.
Dewen Hu, Ling-Li Zeng, Hui Shen
exaly   +2 more sources