Results 221 to 230 of about 587,175 (265)

Sound Source Separation Apparatus And Sound Source Separation Method

The Journal of the Acoustical Society of America, 2011
To shorten an output delay while a high sound source separation performance is ensured when a sound separation process based on an ICA method is performed. A second Fourier transform process execution cycle t2 for obtaining a second frequency-domain signal S1 used as an input signal of a filter process is set shorter than a first Fourier transform ...
Takashi Hiekata, Yohei Ikeda
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Separation of Unknown Number of Sources

IEEE Signal Processing Letters, 2014
We address the problem of blind source separation in acoustic applications where there is no prior knowledge about the number of mixing sources. The presented method employs a mixture of complex Watson distributions in its generative model with a sparse Dirichlet distribution over the mixture weights.
Jalil Taghia, Arne Leijon
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Equivariant adaptive source separation

IEEE Transactions on Signal Processing, 1996
Source separation consists of recovering a set of independent signals when only mixtures with unknown coefficients are observed. This paper introduces a class of adaptive algorithms for source separation that implements an adaptive version of equivariant estimation and is henceforth called equivariant adaptive separation via independence (EASI).
Jean-François Cardoso, Beate H. Laheld
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Sound source separation

2011
When processing a sound recording, sound engineers often face the need to apply specific digital audio effects to certain sounds only. For instance, the remastering of a music recording may require to correct the tuning of a mistuned instrument or relocate that instrument in space without affecting the sound of other instruments.
Evangelista, Gianpaolo, Marchand, Sylvain, Plumbley, Mark, Vincent, Emmanuel   +3 more
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Compressive blind source separation

2010 IEEE International Conference on Image Processing, 2010
The central goal of compressive sensing is to reconstruct a signal that is sparse or compressible in some basis using very few measurements. However reconstruction is often not the ultimate goal and it is of considerable interest to be able to deduce attributes of the signal from the measurements without explicitly reconstructing the full signal.
Yiyue Wu, Yuejie Chi, A. Robert Calderbank   +2 more
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A New Concept for Separability Problems in Blind Source Separation

Neural Computation, 2004
The goal of blind source separation (BSS) lies in recovering the original independent sources of a mixed random vector without knowing the mixing structure. A key ingredient for performing BSS successfully is to know the indeterminacies of the problem—that is, to know how the separating model relates to the original mixing model (separability).
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Blind source separation for BLAST

2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628), 2003
We present a new blind source separation (BSS) approach for Bell Labs layered space-time (BLAST) communication system. The proposed algorithm is derived from the multimodulus algorithm (MMA) and employs the Gram-Schmidt orthogonalization procedure. The basic idea is to adjust the real and imaginary parts of the equalizer matrix separately and then ...
P. Sansrimahachai, Darren B. Ward, Anthony G. Constantinides   +2 more
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Separation of sources of neuromagnetic examinations

Physiological Measurement, 1993
Phantom experiments and computer simulations in combination with the Wiener-Helstrom filter reconstruction technique demonstrate the ability of the improvement of source separation in distributed current arrangements. A spatial region of interest (ROI), in which the current distribution is expected, is defined and discretized into three-dimensional ...
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Bayesian nonstationary source separation

Neurocomputing, 2008
A Bayesian nonstationary source separation algorithm is proposed in this paper to recover nonstationary sources from noisy mixtures. In order to exploit the temporal structure of the data, we use a time-varying autoregressive (TVAR) process to model each source signal.
Qinghua Huang, Jie Yang 0002, Yue Zhou 0005   +2 more
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A new method for source separation

1995 International Conference on Acoustics, Speech, and Signal Processing, 2002
A new adaptive filtering approach to multichannel source separation is presented. The method is based on an extension of traditional single channel blind equalization. This multichannel extension is presented theoretically and the results are demonstrated by simulation using both communications data and speech.
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