A Low-Complexity Linear-in-the-Parameters Nonlinear Filter for Distorted Speech Signals

  • Danilo ComminielloEmail author
  • Michele Scarpiniti
  • Simone Scardapane
  • Raffaele Parisi
  • Aurelio Uncini
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 102)


In this paper, the problem of the online modeling of nonlinear speech signals is addressed. In particular, the goal of this work is to provide a nonlinear model yielding the best tradeoff between performance results and required computational resources. Functional link adaptive filters were proved to be an effective model for this problem, providing the best performance when trigonometric expansion is used as a nonlinear transformation. Here, a different functional expansion is adopted based on the Chebyshev polynomials in order to reduce the overall computational complexity of the model, while achieving good results in terms of perceived quality of processed speech. The proposed model is assessed in the presence of nonlinearities for both simulated and real speech signals.


Nonlinear modeling Functional links Chebyshev polynomials Loudspeaker distortions Nonlinear system identification 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Danilo Comminiello
    • 1
    Email author
  • Michele Scarpiniti
    • 1
  • Simone Scardapane
    • 1
  • Raffaele Parisi
    • 1
  • Aurelio Uncini
    • 1
  1. 1.Department of Information Engineering, Electronics and Telecommunications (DIET)“Sapienza” University of RomeRomeItaly

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