Loading [a11y]/accessibility-menu.js
Identification of nonlinear stochastic systems described by a reduced complexity Volterra model using an ARGLS algorithm | IEEE Conference Publication | IEEE Xplore

Identification of nonlinear stochastic systems described by a reduced complexity Volterra model using an ARGLS algorithm


Abstract:

This paper proposes a stochastic identification algorithm of a model describing non linear stochastic system. The identified model known as SVD-PARAFAC-Volterra model [1]...Show More

Abstract:

This paper proposes a stochastic identification algorithm of a model describing non linear stochastic system. The identified model known as SVD-PARAFAC-Volterra model [1] results from tensor decomposition of kernels of classical Volterra model. The proposed algorithm uses the Recursive Generalized Least Square (RGLS) method in alternative way to estimate the parameters of the model. The algorithm validation is ensured by simulation results.
Date of Conference: 02-04 May 2012
Date Added to IEEE Xplore: 21 June 2012
ISBN Information:
Conference Location: Rome, Italy

Contact IEEE to Subscribe

References

References is not available for this document.