Results 291 to 300 of about 195,151 (333)

Blind separation of surface EMG signals

Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002
Multiple site measurements with surface EMG electrodes can produce a significant amount of cross-talk, which depends on electrode placement. The "blind separation" techniques can be used to reduce that cross-talk. However the conventional techniques are not very effective if the media causes latencies in signal propagation, which is the case of ...
M.I. Vuskovic, X. Li
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WDM monitoring through blind signal separation

Optical Fiber Communication Conference and Exhibit, 2002
WDM monitoring in optical networks can be carried out after the separation in the electronic domain of the individual baseband channels, from which suitable performance parameters can then be measured. We have proposed to apply blind signal separation based on higher-order statistics.
Y. Feng, V. Zarzoso, A.K. Nandi
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Blind Signal Separation, An Overview

2001
Blind Signal Separation (BSS) is the process of recovering independent signals that correspond to the individual source signals using only observed linear mixtures of these. In an acoustic context, these source signals are correlated in time and are assumed to be independent of each other.
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On blind separation of nonstationary signals

Proceedings of the Eighth International Symposium on Signal Processing and Its Applications, 2005., 2006
In this paper we consider a time-frequency based approach to blind separation of nonstationary signals. In particular, we propose a time-frequency ‘point selection’ algorithm based on multiple hypothesis testing, which allows automatic selection of auto- or cross-source locations on the time-frequency plane.
L.A. Cirillo, A.M. Zoubir
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A Blind Signal Separation Algorithm

2001
This chapter addresses the problem of separating multiple speakers from mixtures of these that are obtained using multiple microphones in a room. A new blind signal separation algorithm is derived which is entirely based on second order statistics. The algorithm can run in off-line or online (adaptive) mode.
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Blind signal separation of convolutive mixtures

The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2004
A novel algorithm is described for the blind separation of signals which have been mixed in a convolutive manner. It involves an initial process of strong decorrelation and spectral equalisation, based entirely on second order statistics. This is followed by the identification of a hidden paraunitary matrix which necessitates the use of higher (fourth)
P.D. Baxter, J.G. McWhirter
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New criteria for blind signal separation

Proceedings of the Tenth IEEE Workshop on Statistical Signal and Array Processing (Cat. No.00TH8496), 2002
The problem of multichannel blind signal deconvolution is considered. The mixing system is supposed to be stable and invertible and the input signals, also called sources, are assumed zero-mean independent and identically distributed (IID) random signals.
N. Thirion-Moreau, E. Moreau
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Sparse Deflations in Blind Signal Separation

2006
We present a new deflation procedure for blind signal separation based on sparsity. It allows, under mild sparsity assumptions, to separate mixtures which could not be separated by ICA methods. We present a new algorithm for sparse deflations and apply it for sparse blind signal separation of mixtures of signals with bounded support.
Pando Georgiev, Danielle Nuzillard, Anca Ralescu   +2 more
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Blind Separation of Acoustic Signals

2001
This chapter presents an overview of criteria and algorithms for the blind separation of linearly mixed acoustic signals. Particular attention is paid to the underlying statistical formulations of various approaches to the convolutive blind signal separation task, and comparisons to other blind inverse problems are made.
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Simultaneous blind signal separation and denoising

2008 International Conference on Computer Engineering & Systems, 2008
This paper deals with the problem of blind separation of denoising. It proposes the application of the discrete wavelet transform as a preprocessing step of denoising prior to the blind separation algorithm. The separation of sinusoidal signals as well as speech signals in a noisy environment is studied with and without the use of the wavelet denoising
H. Hammam, A. E. Abu El-Azm, M. E. Elhalawany, F. E. Abd El-Samie   +3 more
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