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Mixture-model-based signal denoising

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Publication:2477574
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DOI10.1007/S11634-006-0002-8zbMath1131.94008OpenAlexW2081452652MaRDI QIDQ2477574

Etienne Côme, Allou Samé, Latifa Oukhellou, Patrice Aknin

Publication date: 14 March 2008

Published in: Advances in Data Analysis and Classification. ADAC (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11634-006-0002-8


zbMATH Keywords

EM algorithmdenoisingregressionGaussian mixture modelGEM algorithmasymmetrical noise


Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)





Cites Work

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  • A maximum likelihood methodology for clusterwise linear regression
  • The use of mixtures for dealing with non-normal regression errors
  • Exact mean integrated squared error
  • Estimating the dimension of a model
  • Data dependent wavelet thresholding in nonparametric regression with change-point applications
  • Density estimation by wavelet thresholding
  • A theory for multiresolution signal decomposition: the wavelet representation
  • Mixture Models, Outliers, and the EM Algorithm




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