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Robust Filtering Under Minimum Error Entropy Criterion

  • Siyuan Peng
  • , Lujuan Dang
  • , Badong Chen
  • , Jose C. Principe
  • Guangdong University of Technology
  • Xi'an Jiaotong University
  • University of Florida

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

1 Scopus citations

Abstract

Adaptive filtering (AF) techniques have found extensive applications in the domain of radar signal processing. In this chapter, we commence by introducing the minimum error entropy (MEE) criterion. Subsequently, we present two exemplary AF algorithms based on MEE, aimed at enhancing the robustness of conventional AF algorithms. To effectively reduce the computational complexity associated with MEE-based AF algorithms, we further propose the quantized MEE (QMEE) criterion-based AF algorithm, which incorporates QMEE as a substitute for MEE in adaptive filter. We substantiate the efficacy and resilience of our algorithms through comprehensive simulations.

Original languageEnglish
Title of host publicationInformation-Theoretic Radar Signal Processing
Publisherwiley
Pages251-276
Number of pages26
ISBN (Electronic)9781394216956
ISBN (Print)9781394216925
DOIs
StatePublished - 1 Jan 2024

Keywords

  • adaptive filtering
  • low computational complexity
  • minimum error entropy
  • quantized MEE
  • robustness
  • signal processing

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