Results 141 to 150 of about 8,942 (181)

Baseline intestinal microbiota composition influences response to a real-world dietary fiber intervention. [PDF]

NPJ Biofilms Microbiomes
Hoffmann Sardá FA, Giuntini EB, Oliveira A, Souza GS, Prado SBR, Taddei CR, Tadini CC, Bittinger K, Bushman FD, Menezes EW, Hoffmann C.   +10 more
europepmc   +1 more source

Automatic LPI radar waveform recognition of overlapping signals based on vision language model. [PDF]

Sci Rep
Yang P, Li G, Tang H, Zhao Y, Yan H.
europepmc   +1 more source

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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 ...
Andrzej, Cichocki, Sergei L, Shishkin, Toshimitsu, Musha, Zbigniew, Leonowicz, Takashi, Asada, Takayoshi, Kurachi   +5 more
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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), 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
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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), 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
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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
openaire   +2 more sources

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
Hamza Massar, C. Stergiadis, B. Nsiri, T. Belhoussine Drissi, M.A. Klados   +4 more
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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),
Alvin Sahroni, Hendra Setiawan, Erlina Marfianti   +2 more
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‘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
S. Wehr, A. Lombard, H. Buchner, W. Kellermann   +3 more
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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.
Xing-Jie Wu, Yun-an Hu, Ming Li, Ling-Li Zeng, Hui Shen, Dewen Hu   +5 more
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