Convergence analysis of forgetting factor least squares algorithm for ARMAX time-delay models

DOI10.1007/s00034-022-02128-xzbMath1510.93070OpenAlexW4289793194MaRDI QIDQ6040437

Kamel Abderrahim, Saïda Bedoui

Publication date: 17 May 2023

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-022-02128-x

zbMATH Keywords

identificationconvergence analysisleast squaresARMAX modelsample delay

Mathematics Subject Classification ID

System identification (93B30) Least squares and related methods for stochastic control systems (93E24) Delay control/observation systems (93C43)

Cites Work

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• Online identification of multivariable discrete time delay systems using a recursive least square algorithm
• On consistency of recursive least squares identification algorithms for controlled auto-regression models
• Identification and stochastic adaptive control
• Delay estimation via sliding mode for nonlinear time-delay systems
• Moving horizon estimation for ARMAX processes with additive output noise
• A robust global approach for LPV FIR model identification with time-varying time delays
• Convergence and consistency of recursive least squares with variable-rate forgetting
• When is rounding allowed in integer nonlinear optimization?
• Estimation of nonstationary ARMAX models based on the Hannan-Rissanen method
• Modified stochastic gradient identification algorithms with fast convergence rates
• A Multi-Time-Scale Generalization of Recursive Identification Algorithm for ARMAX Systems
• Performance analysis of estimation algorithms of nonstationary ARMA processes
• Self-convergence of weighted least-squares with applications to stochastic adaptive control
• Convergence Analysis of Weighted Stochastic Gradient Identification Algorithms Based on Latest‐Estimation for ARX Models