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Presentation
Evolutionary Algorithms Based Filters for Denoising Signals in Cognitive Radio Systems
EPSCoR (2016)
  • ADNAN QUADRI, University of North Dakota
  • Naima Kaabouch, University of North Dakota
Abstract
In wireless communications, transmitted signals are distorted by noise, interference, path loss, and fading. Traditional communication systems include hardware based filters that are bulky, costly, and can filter only specific frequencies. Next generation communication systems, such as Cognitive Radios, will be reconfigurable and can dynamically adjust their parameters to filter any signal of any frequency. Therefore, this project aims to develop efficient reconfigurable algorithms for filters that meet the requirements of next generation communication systems.  
Keywords
  • Adaptive Filters,
  • Software Defined Radio,
  • Cognitive Radio,
  • Signal Processing,
  • Evolutionary Algorithms,
  • Particle Swarm Optimization,
  • Least Mean Square
Publication Date
Spring April, 2016
Location
Grand Forks, ND, USA
Citation Information
ADNAN QUADRI and Naima Kaabouch. "Evolutionary Algorithms Based Filters for Denoising Signals in Cognitive Radio Systems" EPSCoR (2016)
Available at: http://works.bepress.com/adnan-quadri/1/