Kernel recursive maximum correntropy

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Abstract

In this letter, a robust kernel adaptive algorithm, called the kernel recursive maximum correntropy (KRMC), is derived in kernel space and under the maximum correntropy criterion (MCC). The proposed algorithm is particularly useful for nonlinear and non-Gaussian signal processing, especially when data contain large outliers or disturbed by impulsive noises. The superior performance of KRMC is confirmed by simulation results about short-term chaotic time series prediction in alpha-stable noise environments.

Original languageEnglish
Pages (from-to)11-16
Number of pages6
JournalSignal Processing
Volume117
DOIs
StatePublished - 30 May 2015

Keywords

  • Kernel adaptive filter
  • Kernel recursive maximum correntropy (KRMC)
  • Maximum correntropy criterion (MCC)

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