Steady-state and tracking analysis of a robust adaptive filter with low computational cost

  • Authors:

  • Emilio Soria-Olivas;José D. Martín-Guerrero;Antonio J. Serrano-López;Javier Calpe-Maravilla;Jonathon Chambers

  • Affiliations:

  • Digital Signal Processing Group, Department of Electronic Engineering, University of Valencia, Spain;Digital Signal Processing Group, Department of Electronic Engineering, University of Valencia, Spain;Digital Signal Processing Group, Department of Electronic Engineering, University of Valencia, Spain;Digital Signal Processing Group, Department of Electronic Engineering, University of Valencia, Spain;Centre of Digital Signal Processing, Cardiff School of Engineering, Cardiff University, United Kingdom

  • Venue:
  • Signal Processing
  • Year:
  • 2007

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Abstract

This paper analyses a new adaptive algorithm that is robust to impulse noise and has a low computational load [E. Soria, J.D. Martín, A.J. Serrano, J. Calpe, and J. Chambers, A new robust adaptive algorithm with low computacional cost, Electron. Lett. 42 (1) (2006) 60-62]. The algorithm is based on two premises: the use of the cost function often used in independent component analysis and a fuzzy modelling of the hyperbolic tangent function. The steady-state error and tracking capability of the algorithm are analysed using conservation methods [A. Sayed, Fundamentals of Adaptive Filtering, Wiley, New York, 2003], thus verifying the correspondence between theory and experimental results.