Repository logo
Communities & Collections
Research Outputs
Fundings & Projects
People
Statistics
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. KMITL
  3. Publication
  4. Reduced complexity widely-linear adaptive forgetting-factor inverse square-root RLS algorithm
Loading...
Thumbnail Image

Reduced complexity widely-linear adaptive forgetting-factor inverse square-root RLS algorithm

Author(s)
Sitjongsataporn, Suchada
Wiangtong, Theerayod
Date Issued
July 2, 2018
Type
Conference Paper
DOI
10.1109/ECTICon.2018.08619968
Abstract
A reduced complexity inverse square-root recursive least squares algorithm based on widely-linear mechanism is introduced by adaptive forgetting-factor algorithm. The proposed reduced complexity widely-linear approaches based on inverse square-root recursive least squares algorithm is presented for a relation between widely-linear and reduced complexity scheme. By means of mean square deviation approach, an optimal forgetting-factor scheme is proposed in terms of optimal gain sequence. Adaptive forgetting-factor inverse square-root recursive least squares algorithm is used with regard to an optimal forgetting-factor algorithm. Results of simulation depict that the performance of proposed algorithm is shown similar to widely-linear scheme comparison with the existing algorithm.
Citation
Ecti Con 2018 15th International Conference on Electrical Engineering Electronics Computer Telecommunications and Information Technology, 130-133, 2018
Metrics
Get Involved!
  • Source Code
  • Documentation
  • Slack Channel
Make it your own

DSpace-CRIS can be extensively configured to meet your needs. Decide which information need to be collected and available with fine-grained security. Start updating the theme to match your Institution's web identity.

Need professional help?

The original creators of DSpace-CRIS at 4Science can take your project to the next level, get in touch!

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

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback