Results 281 to 290 of about 195,151 (333)
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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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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.
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.
Tse, Peter W., Zhang, J. Y., Wang, X. J.
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Fetal Magnetocardiographic Signals Extracted by ‘Signal Subspace’ Blind Source Separation
IEEE Transactions on Biomedical Engineering, 2005In this paper, we apply independent component analysis to fetal magnetocardiographic data. In particular, we propose an extension of the "cumulant-based iterative inversion" algorithm to include a two-step "signal subspace" subdivision, which allows the user to control the number of components to be estimated by analyzing the eigenvalues distribution ...
C. Salustri, BARBATI, GIULIA, C. Porcaro
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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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Multichannel blind signal separation and reconstruction
IEEE Transactions on Speech and Audio Processing, 1997The separation of multiple signals from their superposition recorded at several sensors is addressed. The methods employ polyspectra of the sensor data in order to extract the unknown signals and estimate the finite impulse response (FIR) coupling systems via a linear equation based algorithm.
S. Shamsunder, G.B. Giannakis
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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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Blind signal separation: statistical principles
Proceedings of the IEEE, 1998Blind signal separation (BSS) and independent component analysis (ICA) are emerging techniques of array processing and data analysis that aim to recover unobserved signals or "sources" from observed mixtures (typically, the output of an array of sensors), exploiting only the assumption of mutual independence between the signals.
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Blind Separation of Cyclostationary Signals
2009In this paper, we propose a new method for the blind source separation with assuming that the source signals are cyclostationarity. The proposed method exploits the characteristics of cyclostationary signals in the Fraction-of-Time probability framework in order to simultaneously separate all sources without restricting the distribution or the number ...
Nhat Anh Cheviet +3 more
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Blind source separation and signal classification
Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154), 2002We 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
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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, Wayne Wolf
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