Volterra series identification and its applications in structural identification of nonlinear block-oriented systems
From MaRDI portal
Publication:5026785
DOI10.1080/00207721.2020.1781289zbMath1483.93088OpenAlexW3038233516MaRDI QIDQ5026785
No author found.
Publication date: 8 February 2022
Published in: International Journal of Systems Science (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207721.2020.1781289
Cites Work
- Unnamed Item
- On covariance function tests used in system identification
- Block-oriented nonlinear system identification
- The identification of nonlinear biological systems: Wiener and Hammerstein Cascade models
- An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
- Frequency domain identification of Wiener models
- Wavelet basis expansion-based Volterra kernel function identification through multilevel excitations
- On convexification of system identification criteria
- Wiener system identification with generalized orthonormal basis functions
- Wavelet basis expansion-based spatio-temporal Volterra kernels identification for nonlinear distributed parameter systems
- Control of 1-D parabolic PDEs with Volterra nonlinearities. I: Design
- Control of 1D parabolic PDEs with Volterra nonlinearities. II: Analysis
- Regularized nonparametric Volterra kernel estimation
- Structure discrimination in block-oriented models using linear approximations: a theoretic framework
- Adaptive nonlinear system identification. The Volterra and Wiener model approaches.
- Identification of nonlinear aeroelastic systems based on the Volterra theory: progress and opportunities
- Blind maximum likelihood identification of Hammerstein systems
- Structure identification of nonlinear dynamic systems - A survey on input/output approaches
- Nonlinear System Identification
- Fading memory and the problem of approximating nonlinear operators with Volterra series
- Representations of non-linear systems: the NARMAX model
- Frequency domain system identification with missing data
- Non-linear systems in the frequency domain: Energy transfer filters
- Nonlinear system modeling and identification using Volterra‐PARAFAC models
- Frequency domain identification of hammerstein models
