Results 141 to 150 of about 191,485 (185)

Blind source separation and signal classification

Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154), 2002
We address the problem of classifying a digitally modulated signal received after propagation through an unknown frequency-selective channel. Channel dispersion induces intersymbol interference or fading, which must be handled before the modulation format can be classified.
A. Swami, S. Barbarossa, B.M. Sadler
openaire   +1 more source

Blind Signal Separation for Cognitive Radio

Journal of Signal Processing Systems, 2009
Many efforts have been dedicated to cognitive radio research and many schemes have been proposed for cognitive radio in the past few years. Unfortunately, an important piece of cognitive radio, namely, signal separation, is missing. The goal of this paper is to stimulate the research interests of incorporating signal separation into cognitive radio ...
Chia-han Lee, Wayne Wolf
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

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.
openaire   +1 more source

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
openaire   +1 more source

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.
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source