Automatic speech signal segmentation based on the innovation adaptive filter
Ryszard Makowski, Robert Hossa (2014)
International Journal of Applied Mathematics and Computer Science
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Ryszard Makowski, Robert Hossa (2014)
International Journal of Applied Mathematics and Computer Science
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Tomasz Barszcz (2009)
International Journal of Applied Mathematics and Computer Science
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The paper investigates the possibility of decomposing vibration signals into deterministic and nondeterministic parts, based on the Wold theorem. A short description of the theory of adaptive filters is presented. When an adaptive filter uses the delayed version of the input signal as the reference signal, it is possible to divide the signal into a deterministic (gear and shaft related) part and a nondeterministic (noise and rolling bearings) part. The idea of the self-adaptive filter...
Miroslav L. Dukić, Zoran S. Dobrosavljević (1997)
Kybernetika
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Li, Sheng, Wang, Jian Qi, Jing, Xi Jing (2010)
Mathematical Problems in Engineering
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Petr Tichavský, Zbyněk Koldovský (2011)
Kybernetika
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This paper presents a survey of recent successful algorithms for blind separation of determined instantaneous linear mixtures of independent sources such as natural speech or biomedical signals. These algorithms rely either on non-Gaussianity, nonstationarity, spectral diversity, or on a combination of them. Performance of the algorithms will be demonstrated on separation of a linear instantaneous mixture of audio signals (music, speech) and on artifact removal in electroencephalogram...
Chawla, M.P.S. (2007)
Computational & Mathematical Methods in Medicine
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Rastislav Lukac, Bogdan Smołka (2003)
International Journal of Applied Mathematics and Computer Science
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In this paper a novel method of noise reduction in color images is presented. The new technique is capable of attenuating both impulsive and Gaussian noise, while preserving and even enhancing the sharpness of the image edges. Extensive simulations reveal that the new method outperforms significantly the standard techniques widely used in multivariate signal processing. In this work we apply the new noise reduction method for the enhancement of the images of the so called gene chips....
Ewa Świercz (2010)
International Journal of Applied Mathematics and Computer Science
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A new supervised classification algorithm of a heavily distorted pattern (shape) obtained from noisy observations of nonstationary signals is proposed in the paper. Based on the Gabor transform of 1-D non-stationary signals, 2-D shapes of signals are formulated and the classification formula is developed using the pattern matching idea, which is the simplest case of a pattern recognition task. In the pattern matching problem, where a set of known patterns creates predefined classes,...
S. Nakamori, A. Hermoso, J. Jiménez, J. Linares (2005)
Extracta Mathematicae
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In this paper two recursive algorithms are proposed and compared as a solution of the least mean-squared error linear filtering problem of a wide-sense stationary scalar signal from uncertain observations perturbed by white and coloured additive noises. Considering that the state-space model of the signal is not available and that the variables modelling the uncertainty are not independent, the proposed algorithms are derived by using covariance information. The difference between both...