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An adaptive network for blind separation of independent signals
1993 IEEE International Symposium on Circuits and Systems, 2002The problem of separating two or several independent signals (or independent speakers) from an array of sensors within the framework of adaptive systems is formulated. The delayed signals are modeled as a dynamic state model. The crucial aspect of this formulation is to quantify the property of independence of signals in terms of an explicit function ...
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Blind signal separation for convolved nonstationary signals
Electronics and Communications in Japan (Part III: Fundamental Electronic Science), 2000International ...
Kawamoto, Mitsuru +4 more
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Bootstrap: a fast blind adaptive signal separator
[Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing, 1992A fast multidimensional adaptive algorithm, Bootstrap, is proposed for multiple signal separation. It separates multiple uncorrelated signals imposed on each other. The bootstrap adaptive algorithm, which does not require training sequences, uses an optimization criteria that is based on minimization of output signal correlations.
Abdulkadir Dinc, Yeheskel Bar-Ness
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Convolutive Blind Signal Separation With Post-Processing
IEEE Transactions on Speech and Audio Processing, 2004A new subband based speech enhancement scheme is presented. It integrates spatial and temporal signal processing methods to enhance speech signals in a noisy environment. The approach makes use of the popular blind signal separation (BSS) to spatially separate the target signal from the interference.
Siow Yong Low +2 more
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Blind separation of convolutive mixtures of cyclostationary signals
International Journal of Adaptive Control and Signal Processing, 2004AbstractAn adaptive blind source separation algorithm for the separation of convolutive mixtures of cyclostationary signals is proposed. The algorithm is derived by applying natural gradient iterative learning to a novel cost function which is defined according to the wide sense cyclostationarity of signals and can be deemed as a new member of the ...
Wang, W +3 more
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Blind Source Separation of Temporal Correlated Signals
2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System, 2007In this paper, we present a new framework for blind source separation of temporal correlated signals. In general, temporal correlated signals are not independent which means the independence assumption for independent component analysis method is not satisfied.
Bin Xia 0004, Hong Xie 0001
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A modified infomax algorithm for blind signal separation
Neurocomputing, 2006Abstract We present a new algorithm to perform blind signal separation (BSS), which takes a trade-off between the ordinary gradient infomax algorithm and the natural gradient infomax algorithm. Analyzing the algorithm, we show that desired equilibrium points are locally stable by choosing appropriate score functions and step sizes.
Hyung-Min Park +2 more
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Blind separation of temporomandibular joint sound signals
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999In order to develop a cheap, efficient and reliable diagnostic tool for the detection of temporomandibular joint disorders (TMD), sounds from the temporomandibular joint (TMJ) are recorded using a pair of microphone inserted in the auditory canals. However, the TMJ sounds originating from one side of the head can also be picked up by a microphone at ...
Yinchao Guo +2 more
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A blind signal separation method for multiuser communications
IEEE Transactions on Signal Processing, 1997A new approach based on the constant modulus (CM) criterion is proposed to separate instantaneous linear mixtures of signals using a linear memoryless multiple input multiple output (MIMO) system. Even though a nonconvex cost function is minimized, analyses show that minima correspond to parameter settings where perfect separation is achieved.
Luis Castedo +2 more
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A Blind Signal Separation Algorithm
2001This 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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