Recursive parameter identification of the dynamical models for bilinear state space systems
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Recursive parameter identification of the dynamical models for bilinear state space systems
Authors
Keywords
Dynamical system, Parameter estimation, State estimation, Multi-innovation theory, State space model, Bilinear system
Journal
NONLINEAR DYNAMICS
Volume 89, Issue 4, Pages 2415-2429
Publisher
Springer Nature
Online
2017-06-15
DOI
10.1007/s11071-017-3594-y
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Parameter estimation algorithms for dynamical response signals based on the multi-innovation theory and the hierarchical principle
- (2017) Ling Xu et al. IET Signal Processing
- Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering
- (2017) Feng Ding et al. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
- A multi-innovation state and parameter estimation algorithm for a state space system with d-step state-delay
- (2017) Ling Xu et al. SIGNAL PROCESSING
- Hierarchical parameter estimation for a class of MIMO Hammerstein systems based on the reframed models
- (2016) Dongqing Wang APPLIED MATHEMATICS LETTERS
- A novel parameter separation based identification algorithm for Hammerstein systems
- (2016) Yawen Mao et al. APPLIED MATHEMATICS LETTERS
- Least Squares-Based Iterative Identification Methods for Linear-in-Parameters Systems Using the Decomposition Technique
- (2016) Feifei Wang et al. CIRCUITS SYSTEMS AND SIGNAL PROCESSING
- Recursive Least Squares and Multi-innovation Stochastic Gradient Parameter Estimation Methods for Signal Modeling
- (2016) Ling Xu et al. CIRCUITS SYSTEMS AND SIGNAL PROCESSING
- Array Factor Forming for Image Reconstruction of One-Dimensional Nonuniform Aperture Synthesis Radiometers
- (2016) Li Feng et al. IEEE Geoscience and Remote Sensing Letters
- Performance analysis of the generalised projection identification for time-varying systems
- (2016) Feng Ding et al. IET Control Theory and Applications
- Filtering-based iterative identification for multivariable systems
- (2016) Yanjiao Wang et al. IET Control Theory and Applications
- Parameter estimation algorithms for multivariable Hammerstein CARMA systems
- (2016) Dongqing Wang et al. INFORMATION SCIENCES
- Fault diagnosis method based on FFT-RPCA-SVM for Cascaded-Multilevel Inverter
- (2016) Tianzhen Wang et al. ISA TRANSACTIONS
- A T-wave alternans assessment method based on least squares curve fitting technique
- (2016) Xiangkui Wan et al. MEASUREMENT
- An adaptive confidence limit for periodic non-steady conditions fault detection
- (2016) Tianzhen Wang et al. MECHANICAL SYSTEMS AND SIGNAL PROCESSING
- Image noise smoothing using a modified Kalman filter
- (2016) Jian Pan et al. NEUROCOMPUTING
- The damping iterative parameter identification method for dynamical systems based on the sine signal measurement
- (2016) Ling Xu SIGNAL PROCESSING
- The auxiliary model based hierarchical gradient algorithms and convergence analysis using the filtering technique
- (2016) Yanjiao Wang et al. SIGNAL PROCESSING
- Identification of nonlinear cascade systems with output hysteresis based on the key term separation principle
- (2015) Jozef Vörös APPLIED MATHEMATICAL MODELLING
- A subspace-based identification of Wiener–Hammerstein benchmark model
- (2015) Hajime Ase et al. CONTROL ENGINEERING PRACTICE
- Optimal bilinear observers for bilinear state-space models by interaction matrices
- (2015) Minh Q. Phan et al. INTERNATIONAL JOURNAL OF CONTROL
- Application of the Newton iteration algorithm to the parameter estimation for dynamical systems
- (2015) Ling Xu JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
- Improved least squares identification algorithm for multivariable Hammerstein systems
- (2015) Dongqing Wang et al. JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
- Parameters estimation, mixed synchronization, and antisynchronization in chaotic systems
- (2014) Chunni Wang et al. COMPLEXITY
- Unbiased Recursive Least-Squares Estimation Utilizing Dichotomous Coordinate-Descent Iterations
- (2014) IEEE TRANSACTIONS ON SIGNAL PROCESSING
- Linear state representations for identification of bilinear discrete-time models by interaction matrices
- (2014) Francesco Vicario et al. NONLINEAR DYNAMICS
- Multi-innovation stochastic gradient identification for Hammerstein controlled autoregressive autoregressive systems based on the filtering technique
- (2014) Yawen Mao et al. NONLINEAR DYNAMICS
- Parameter estimation and controller design for dynamic systems from the step responses based on the Newton iteration
- (2014) Ling Xu et al. NONLINEAR DYNAMICS
- State filtering and parameter estimation for state space systems with scarce measurements
- (2014) Feng Ding SIGNAL PROCESSING
- State estimation with partially observed inputs: A unified Kalman filtering approach
- (2013) Baibing Li AUTOMATICA
- Least squares algorithm for an input nonlinear system with a dynamic subspace state space model
- (2013) Dongqing Wang et al. NONLINEAR DYNAMICS
- Performance Analysis of the Auxiliary Model-Based Stochastic Gradient Parameter Estimation Algorithm for State-Space Systems with One-Step State Delay
- (2012) Feng Ding et al. CIRCUITS SYSTEMS AND SIGNAL PROCESSING
- Identification of discrete-time bilinear systems through equivalent linear models
- (2012) N. Berk Hizir et al. NONLINEAR DYNAMICS
- System identification of nonlinear state-space models
- (2010) Thomas B. Schön et al. AUTOMATICA
- Complete synchronization, phase synchronization and parameters estimation in a realistic chaotic system
- (2010) Jun Ma et al. Communications in Nonlinear Science and Numerical Simulation
- Identification of Bilinear Systems With White Noise Inputs: An Iterative Deterministic-Stochastic Subspace Approach
- (2009) P.L. dos Santos et al. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
- Blind maximum likelihood identification of Hammerstein systems
- (2008) Laurent Vanbeylen et al. AUTOMATICA
Create your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create NowAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started