Identification of Volterra-PARAFAC models using partial update LMS algorithms

@article{Ahmed2015IdentificationOV,
  title={Identification of Volterra-PARAFAC models using partial update LMS algorithms},
  author={Zouhour Ben Ahmed and G{\'e}rard Favier and Nabil Derbel},
  journal={2015 7th International Conference on Modelling, Identification and Control (ICMIC)},
  year={2015},
  pages={1-4}
}
Volterra models can be used to represent a nonlinear systems with vanishing memory. The main drawback of these models is their huge number of parameters to be estimated. To reduce this parametric complexity, we can consider Volterra kernels of order (p > 2) as symmetric tensors and we use a parallel factor (PARAFAC) decomposition of the kernels to derive Volterra-PARAFAC models. In this paper, we present partial update LMS algorithms for identifying nonlinear third-order Volterra-PARAFAC models… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-10 of 10 references

Modèles de Volterra à complexité réduite : Estimation paramétrique et application à l’égalisation des canaux de communication

  • A. Y. KIBANGOU
  • Ph.D. dissertation, Université Nice-Sophia…
  • 2005
1 Excerpt

Adaptive predictive coding of speech by means of volterra predictors

  • E. Mumolo, D. Francescato
  • Proc. of IEEE Winter Workshop on Nonlinear…
  • 1993
1 Excerpt

Similar Papers

Loading similar papers…