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Time-frequency learning machines

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Abstract

Over the last decade, the theory of reproducing kernels has made a major breakthrough in the field of pattern recognition. It has led to new algorithms, with improved performance and lower computational cost, for non-linear analysis in high dimensional feature spaces. Our paper is a further contribution which extends the framework of the so-called kernel learning machines to time-frequency analysis, showing that some specific reproducing kernels allow these algorithms to operate in the time-frequency domain. This link offers new perspectives in the field of non-stationary signal analysis, which can benefit from the developments of pattern recognition and Statistical Learning Theory.
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Dates and versions

ensl-00118896 , version 1 (07-12-2006)

Identifiers

  • HAL Id : ensl-00118896 , version 1

Cite

Paul Honeiné, Cédric Richard, Patrick Flandrin. Time-frequency learning machines. 2006. ⟨ensl-00118896⟩
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