Results 221 to 230 of about 26,456 (261)
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2019
The filters in previous chapters utilized some features of the image and/or noise to attenuate noise.
Abdullatif Al-Shuhail, Saleh Al-Dossary
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The filters in previous chapters utilized some features of the image and/or noise to attenuate noise.
Abdullatif Al-Shuhail, Saleh Al-Dossary
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Denoising Human Speech Signals Using Chaoslike Features
Physical Review Letters, 2000A local projective noise reduction scheme, originally developed for low-dimensional stationary deterministic chaotic signals, is successfully applied to human speech. This is possible by exploiting properties of the speech signal which resemble structure exhibited by deterministic dynamical systems.
Hegger, R., Kantz, H., Matassini, L.
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Improved VC-based signal denoising
IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222), 2002Signal denoising is closely related to function estimation from noisy samples. Vapnik-Chervonenkis (VC) theory provides a general framework for estimation of dependencies from finite samples. This theory emphasizes model complexity control according to the structural risk minimization inductive principle, which considers a nested set of models of ...
null Jie Shao, V. Cherkassky
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Denoising 1D signal using wavelets
International Journal of Intelligent Systems Technologies and Applications, 2020Signal denoising is one of the most important areas in signal processing. In the present paper, we have denoised a 1D piecewise constant (PWC) signal corrupted by additive white Gaussian noise (AWGN) using the thresholded Haar wavelet denoising method. The central idea of the wavelet transform is the multiresolution decomposition of signals.
Prateep Upadhay +2 more
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Bioacoustic signal denoising: a review
Artificial Intelligence Review, 2020Animal biodiversity has been experiencing rapid decline due to various reasons such as habitat loss and degradation, invasive species, and environment pollution. Recent advances in acoustic sensors provide a novel way to monitor animals through investigating collected bioacoustic recordings.
Jie Xie, Juan G. Colonna, Jinglan Zhang
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Noise variance in signal denoising
2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)., 2004In the thresholding method of denoising the optimum threshold is obtained as a function of additive noise variance. In practical problems, where the variance of the noise is unknown, the first step is to estimate the noise variance. The estimated noise variance is then implemented in calculation of the optimum threshold.
S. Beheshti, M.A. Dahleh
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Signal denoising with average sampling
Digital Signal Processing, 2012Based on the theory of average sampling, we present a new algorithm to reconstruct bandlimited signals from sampled values in the presence of zero mean, independent and identically distributed random noises. Numerical results show that our algorithm has good performance on denoising.
Qingyue Zhang, Ling Wang, Wenchang Sun
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Interferometric signal denoised by wavelets
OCEANS 2006, 2006This paper concerns the possibilities for side scan sonar to determine the bathymetry. High definition sea-bottom imaging is the primary task for new side scan sonars; nevertheless, these systems are also able to estimate the relief with a definition equal to the pixel resolution of conventional imaging sonar, through an interferometric multisensors ...
Christophe Sintes +2 more
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2009 IEEE Circuits and Systems International Conference on Testing and Diagnosis, 2009
Although the empirical mode decomposition (EMD) is a new time-frequency analysis technique, it has a wide-ranging application in last decade. In this paper, we proposed a combined signal denoising method based on EMD and use the denoising method to recover the corrupted test signal. Three traditional denoising methods are combined with EMD to implement
Chengti Huang, Houjun Wang, Bing Long
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Although the empirical mode decomposition (EMD) is a new time-frequency analysis technique, it has a wide-ranging application in last decade. In this paper, we proposed a combined signal denoising method based on EMD and use the denoising method to recover the corrupted test signal. Three traditional denoising methods are combined with EMD to implement
Chengti Huang, Houjun Wang, Bing Long
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ICA based ECG signal denoising
2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2013Significant diagnostic information in healthcare is obtained from Electrocardiogram (ECG) signals, so improvements in their analysis are also of growing importance. In the field of signal processing, the rapidly developing signal technology and flourishing variety of algorithms have proved successful targets for research in healthcare.
Mrinal Phegade, P. Mukherji
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