System Identification Based on Hammerstein Models Using Cubic Splines

Gasparini M, Primavera A, Romoli L, Cecchi S, Piazza F. System Identification Based on Hammerstein Models Using Cubic Splines. In: AES Convention 134. Audio Engineering Society; 2013. Paper 8913. Available from: https://aes.org/publications/elibrary-page/?id=16813

@inproceedings{Gasparini2013_16813,
  author = {Gasparini, Michele and Primavera, Andrea and Romoli, Laura and Cecchi, Stefania and Piazza, Francesco},
  title = {{System Identification Based on Hammerstein Models Using Cubic Splines}},
  booktitle = {AES Convention 134},
  note = {Paper 8913},
  year = {2013},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=16813}
}

TY  - CPAPER
TI  - System Identification Based on Hammerstein Models Using Cubic Splines
AU  - Gasparini, Michele
AU  - Primavera, Andrea
AU  - Romoli, Laura
AU  - Cecchi, Stefania
AU  - Piazza, Francesco
T2  - AES Convention 134
M1  - Paper 8913
PY  - 2013
DA  - 2013/05/06
UR  - https://aes.org/publications/elibrary-page/?id=16813
PB  - Audio Engineering Society
LA  - en
AB  - Nonlinear system modeling plays an important role in the field of digital audio systems whereas most of the real-world devices show a nonlinear behavior. Among nonlinear models, Hammerstein systems are particular nonlinear systems composed of a static nonlinearity cascaded with a linear filter. In this paper a novel approach for the estimation of the static nonlinearity is proposed based on the introduction of an adaptive CatmullRom cubic spline in order to overcome problems related to the adaptation of high-order polynomials necessary for identifying highly nonlinear systems. Experimental results confirm the effectiveness of the approach, making also comparisons with existing techniques of the state of the art.
ER  -