Repository logo
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Scholalry Output
  3. Publications
  4. Robust and sparsity-aware adaptive filters: A Review
 
  • Details

Robust and sparsity-aware adaptive filters: A Review

Source
Signal Processing
ISSN
01651684
Date Issued
2021-12-01
Author(s)
Kumar, Krishna
Pandey, Rajlaxmi
Karthik, M. L.N.S.
Bhattacharjee, Sankha Subhra
George, Nithin V.  
DOI
10.1016/j.sigpro.2021.108276
Volume
189
Abstract
An exhaustive review of adaptive signal processing schemes which are robust, sparsity-aware and robust as well as sparsity-aware has been carried out in this paper. Conventional robust learning approaches as well as the ones based on information theoretic methods have been included in the review. Further, adaptive filtering schemes which take advantage of the sparse nature of the system impulse responses have been reviewed, including the ones which are also robust. The cost functions used in these algorithms have been summarized and a timeline of algorithm development in this area has been added to provide an excellent overview on the topic.
Unpaywall
URI
https://d8.irins.org/handle/IITG2025/25186
Subjects
Adaptive filter | Correntropy criterion | Robust learning | Sparsity-aware adaptive filter
IITGN Knowledge Repository Developed and Managed by Library

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify