Results 11 to 20 of about 48,878 (307)
Denoising Method Based on Sparse Representation for WFT Signal
Journal of Sensors, 2014 Affected by external noise and various nature disturbances, Wheel Force Transducer (WFT) signal may be completely submerged, and the sensitivity and the reliability of measurement can be strongly decreased. In this paper, a new wavelet packet denoising method based on sparse representation is proposed to remove the noises from WFT signal.
Xu Chen 0008, Guoyu Lin, Yuxin Zhang
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A novel sparse representation algorithm for AIS real-time signals
EURASIP Journal on Wireless Communications and Networking, 2018 Sparse representation of signals based on a redundant dictionary is a new signal representation theory. Recent research activities in this field have concentrated mainly on the study of dictionary design and sparse decomposition algorithms.
Shuaiheng Huai, Shufang Zhang
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Sparse representations in audio & music: from coding to source separation [PDF]
, 2010 —Sparse representations have proved a powerful toolin the analysis and processing of audio signals and already lieat the heart of popular coding standards such as MP3 andDolby AAC.
Davies, ME +15 more
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Bayesian Orthogonal Component Analysis for Sparse Representation [PDF]
, 2010 This paper addresses the problem of identifying a lower dimensional space where observed data can be sparsely represented. This undercomplete dictionary learning task can be formulated as a blind separation problem of sparse sources linearly mixed with ...
Nicolas Dobigeon +3 more
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Sparse Representation of Group-Wise FMRI Signals [PDF]
, 2013 The human brain function involves complex processes with population codes of neuronal activities. Neuroscience research has demonstrated that when representing neuronal activities, sparsity is an important characterizing property. Inspired by this finding, significant amount of efforts from the scientific communities have been recently devoted to ...
Jinglei Lv +8 more
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Journal of Mathematics, 2022 Aiming at the problems of poor classification effect, low accuracy, and long time in the current automatic classification methods of music genres, an automatic classification method of music genres based on deep belief network and sparse representation ...
Lina Pan
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Voxel selection in fMRI data analysis based on sparse representation [PDF]
, 2009 Multivariate pattern analysis approaches toward detection of brain regions from fMRI data have been gaining attention recently. In this study, we introduce an iterative sparse-representation-based algorithm for detection of voxels in functional MRI (fMRI)
Namburi, Praneeth +5 more
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Estimation of LFM signal parameters using RD compressed sampling and the DFRFT dictionary
EURASIP Journal on Advances in Signal Processing, 2023 In this paper, a method combining random demodulator (RD) and discrete fractional Fourier transform (DFRFT) dictionary is suggested to directly estimate the parameters of linear frequency modulation (LFM) signals from compressed sampling data. First, the
Shuo Meng, Chen Meng, Cheng Wang
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Xibei Gongye Daxue Xuebao, 2020 Aiming at the direction of arrival (DOA) estimation of coherent signals in vector hydrophone array, an iterative sparse covariance matrix fitting algorithm is proposed.
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Judgement of unvoiced and voiced pronunciation based on sparse feature with DCT dictionary [PDF]
MATEC Web of Conferences, 2019 The judgment of unvoiced and voiced sound based on sparse representation in DCT dictionary is implemented. Human pronunciation can be mainly divided into unvoiced and voiced sound.
Wang Lianzi +2 more
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