Parameter identification of ARX models based on modified momentum gradient descent algorithm

DOI10.1155/2020/9537075zbMath1441.93319OpenAlexW3035784675MaRDI QIDQ781781

Yingjiao Rong, Jing Chen, Quan Tu

Publication date: 18 July 2020

Published in: Complexity (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2020/9537075

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

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Cites Work

• Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
• Hierarchical multi-innovation stochastic gradient algorithm for Hammerstein nonlinear system modeling
• Decomposition based least squares iterative identification algorithm for multivariate pseudo-linear ARMA systems using the data filtering
• Performance analysis of multi-innovation gradient type identification methods
• A back propagation algorithm to estimate the parameters of nonlinear dynamic rational models.
• Nonlinear modeling and control approach to magnetic levitation ball system using functional weight RBF network-based state-dependent ARX model
• Two-stage least squares based iterative estimation algorithm for CARARMA system modeling
• Model recovery for Hammerstein systems using the hierarchical orthogonal matching pursuit method
• Combined state and least squares parameter estimation algorithms for dynamic systems
• Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems
• Model recovery for Hammerstein systems using the auxiliary model based orthogonal matching pursuit method
• Lower error bounds for the stochastic gradient descent optimization algorithm: sharp convergence rates for slowly and fast decaying learning rates
• Conjugate gradient least squares algorithm for solving the generalized coupled Sylvester-conjugate matrix equations
• Convergence time calculation for supertwisting algorithm and application for nonaffine nonlinear systems
• Homeomorphism mapping based neural networks for finite time constraint control of a class of nonaffine pure-feedback nonlinear systems
• An enhanced linear Kalman filter (EnLKF) algorithm for parameter estimation of nonlinear rational models
• Partially Coupled Stochastic Gradient Identification Methods for Non-Uniformly Sampled Systems
• Hierarchical parameter and state estimation for bilinear systems
• The innovation algorithms for multivariable state‐space models
• The filtering‐based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle
• Hierarchical Least Squares Identification for Linear SISO Systems With Dual-Rate Sampled-Data