Results 231 to 240 of about 2,961,150 (281)
A frequency domain blind signal separation method based on decorrelation
IEEE Transactions on Signal Processing, 2002 This paper addresses the issue of separating multiple speakers from mixtures of these that are obtained using multiple microphones in a room. An adaptive blind signal separation algorithm, which is entirely based on second-order statistics, is derived ...
Sommen, PCW Piet +3 more
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Blind signal separation using QMF
2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS), 2015Blind signal separation method is the method that the source signals are obtained by separating only the mixed signals. Generally, separation precision is lower when blind signal separation method is used for the sound signals. It is the cause that the power of the sound signals is concentrated in the low-frequency band.
Kazuaki Matsushima +2 more
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Blind Signal Separation for Cognitive Radio
Journal of Signal Processing Systems, 2009Many 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, Marilyn Wolf
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2019 International SoC Design Conference (ISOCC), 2019
We take advantage of the relative gradient method and the bound component analysis algorithm to propose the relativegradient bound component analysis algorithm in this paper. This algorithm does not need to compute the inverse matrix and the covariance matrix. It can succesfully separate the mixed pictures without whitening. The time complexity and the
Chuen-Yau Chen +3 more
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We take advantage of the relative gradient method and the bound component analysis algorithm to propose the relativegradient bound component analysis algorithm in this paper. This algorithm does not need to compute the inverse matrix and the covariance matrix. It can succesfully separate the mixed pictures without whitening. The time complexity and the
Chuen-Yau Chen +3 more
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Sparse Deflations in Blind Signal Separation
2006We 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 G. Georgiev +2 more
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A Note on Stone's Conjecture of Blind Signal Separation
Neural Computation, 2005Stone's method is one of the novel approaches to the blind source separation (BSS) problem and is based on Stone's conjecture. However, this conjecture has not been proved. We present a simple simulation to demonstrate that Stone's conjecture is incorrect.
Shengli Xie, Zhaoshui He, Yuli Fu 0001
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Blind Signal Separation with Speech Enhancement
2013A new speech enhancement architecture using convolutive blind signal separation (CBSS) and subspace-based speech enhancement is presented. The spatial and spectral information are integrated to enhance the target speech signal and suppress both interference noise and background noise.
Chang-Hong Lin +6 more
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Blind signal separation revisited
Proceedings of the 36th IEEE Conference on Decision and Control, 2002Complex control and decision systems are very often confronted with an extensive amount of information about their environment from various sensors such as video cameras, etc. Hence, extraction of non-redundant signals from the available sensor information has become an important task in many control and decision problems.
D. Obradovic, G. Deco
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Blind Signal Separation and Blind Deconvolution
2001This chapter introduces basic concepts, criteria, and algorithms for Blind signal separation (BSS) and blind deconvolution and explores relationships between the BSS and blind deconvolution tasks. The chapter considers open issues and challenges within these related fields. BSS is sometimes used interchangeably with independent component analysis (ICA),
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Journal of Vibration and Control, 2006
Many advanced techniques have been developed for diagnosis of machine faults caused by vibration. They are effective if the inspected vibration is well isolated from interference caused by vibrations from adjacent components. However, the components of manufacturing machines are numerous, small, and packed closely together. Thus the signal collected by
Tse, Peter W., Zhang, J. Y., Wang, X. J.
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Many advanced techniques have been developed for diagnosis of machine faults caused by vibration. They are effective if the inspected vibration is well isolated from interference caused by vibrations from adjacent components. However, the components of manufacturing machines are numerous, small, and packed closely together. Thus the signal collected by
Tse, Peter W., Zhang, J. Y., Wang, X. J.
openaire +1 more source