Some stochastic gradient algorithms for Hammerstein systems with piecewise linearity
From MaRDI portal
Publication:2697720
DOI10.1007/s00034-020-01554-zOpenAlexW3091465500MaRDI QIDQ2697720
Yan Pu, Jing Chen, Yongqing Yang
Publication date: 13 April 2023
Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s00034-020-01554-z
Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12) Stochastic approximation (62L20)
Related Items
Cites Work
- Robust EM kernel-based methods for linear system identification
- Data filtering based forgetting factor stochastic gradient algorithm for Hammerstein systems with saturation and preload nonlinearities
- Identification of multiple-input single-output Hammerstein models using Bézier curves and Bernstein polynomials
- Parameter identification of Wiener systems with multisegment piecewise-linear nonlinearities
- An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems
- Identification of linear systems with hard input nonlinearities of known structure
- Biased compensation recursive least squares-based threshold algorithm for time-delay rational models via redundant rule
- Multi-step-length gradient iterative algorithm for equation-error type models
- On a robust Aitken-Newton method based on the Hermite polynomial
- Hammerstein-Wiener system estimator initialization
- Review of stability and stabilization for impulsive delayed systems
- Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems
- Generalized exponential autoregressive models for nonlinear time series: stationarity, estimation and applications
- A new Aitken type method for accelerating iterative sequences
- A recursive parametric estimation algorithm of multivariable nonlinear systems described by Hammerstein mathematical models
- Recursive identification of bilinear time-delay systems through the redundant rule
- Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model
- Iterative parameter estimation for signal models based on measured data
- Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise
- Maximum likelihood identification of Wiener models
- Recursive least squares and multi-innovation stochastic gradient parameter estimation methods for signal modeling
- Gradient based estimation algorithm for Hammerstein systems with saturation and dead-zone nonlinearities
- Recursive identification of time-varying systems: self-tuning and matrix RLS algorithms
- A survey on piecewise-linear models of regulatory dynamical systems
- Modified stochastic gradient identification algorithms with fast convergence rates
- Fixed-time control of delayed neural networks with impulsive perturbations
- Adaptive parameter estimation for a general dynamical system with unknown states
- Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems
- Parameter estimation for block‐oriented nonlinear systems using the key term separation
- The innovation algorithms for multivariable state‐space models
- Global exponential stabilization of impulsive neural networks with unbounded continuously distributed delays
- Highly computationally efficient state filter based on the delta operator
- The conjugate-gradient method for optimal control problems with undetermined final time†
