Nonlinear system modeling and identification using Volterra-PARAFAC models
نویسندگان
چکیده
منابع مشابه
Nonlinear system modeling and identification using Volterra-PARAFAC models
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau...
متن کاملOn nonlinear amplifier modeling and identification using baseband Volterra-Parafac models
The baseband Volterra–Parafac model is a useful tool to represent a nonlinear communication channel with a parametric complexity reduced with respect to the full Volterra model. In this paper we include additional symmetry properties of real power amplifier kernels in the equivalent baseband Volterra-Parafac approach in order to gain a further reduction in the number of parameters. To illustrat...
متن کاملA Nonlinear Thermal Process Modeling and Identification using a fourth-order S-PARAFAC Volterra Model
This paper proposes a new reduced complexity Volterra model called S-PARAFAC-Volterra. The proposed model is yielded by using the symmetry property of the Volterra kernels and their tensor decomposition using the PARAFAC technique. It takes advantage from previous results where an algorithm for the estimation of the memory and the order of the Volterra model has been presented. The proposed mod...
متن کاملReduced Complexity Volterra Models for Nonlinear System Identification
A broad class of nonlinear systems and filters can be modeled by the Volterra series representation. However, its practical use in nonlinear system identification is sometimes limited due to the large number of parameters associated with the Volterra filter’s structure. The parametric complexity also complicates design procedures based upon such a model. This limitation for system identificatio...
متن کاملNonlinear System Identification Based on Reduced Complexity Volterra Models
Conventional Volterra series model is hardly applied to engineering practice due to its parametric complexity and estimation difficulty. To solve this problem, nonlinear system identification using reduced complexity Volterra models is proposed. Since the nonlinear components often play a secondary role compared to the dominant, linear component of the system, they spend the most of identificat...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Adaptive Control and Signal Processing
سال: 2011
ISSN: 0890-6327
DOI: 10.1002/acs.1272