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Filtered auxiliary model recursive generalized extended parameter estimation methods for Box–Jenkins systems by means of the filtering identification idea

International journal of robust and nonlinear control, 2023-07, Vol.33 (10), p.5510-5535

2023

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An efficient recursive identification algorithm for multilinear systems based on tensor decomposition

International journal of robust and nonlinear control, 2021-11, Vol.31 (16), p.7920-7936

2021

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A novel nonlinear optimization method for fitting a noisy Gaussian activation function

International journal of adaptive control and signal processing, 2022-03, Vol.36 (3), p.690-707

2022

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The innovation algorithms for multivariable state‐space models

International journal of adaptive control and signal processing, 2019-11, Vol.33 (11), p.1601-1618

2019

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Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory

International journal of robust and nonlinear control, 2022-09, Vol.32 (13), p.7304-7318

2022

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Auxiliary model‐based multi‐innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity

International journal of adaptive control and signal processing, 2022-03, Vol.36 (3), p.521-540

2022

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Multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique

International journal of robust and nonlinear control, 2023-09, Vol.33 (13), p.7755-7773

2023

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Filtered generalized iterative parameter identification for equation‐error autoregressive models based on the filtering identification idea

International journal of adaptive control and signal processing, 2024-04, Vol.38 (4), p.1363-1385

2024

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Hierarchical iterative identification algorithms for a nonlinear system with dead‐zone and saturation nonlinearity based on the auxiliary model

International journal of adaptive control and signal processing, 2023-07, Vol.37 (7), p.1866-1892

2023

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Auxiliary model‐based recursive least squares algorithm for two‐input single‐output Hammerstein output‐error moving average systems by using the hierarchical identification principle

International journal of robust and nonlinear control, 2022-09, Vol.32 (13), p.7575-7593

2022

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Data filtering based multi‐innovation gradient identification for bilinear systems with colored noise

International journal of adaptive control and signal processing, 2023-07, Vol.37 (7), p.1940-1960

Wu, Xiaoqiang

2023

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Three‐stage multi‐innovation parameter estimation for an exponential autoregressive time‐series model with moving average noise by using the data filtering technique

International journal of robust and nonlinear control, 2021-01, Vol.31 (1), p.166-184

2021

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Identification of the nonlinear systems based on the kernel functions

International journal of robust and nonlinear control, 2021-09, Vol.31 (14), p.6917-6933

2021

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The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise

International journal of adaptive control and signal processing, 2020-10, Vol.34 (10), p.1321-1340

2020

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Multi‐innovation Newton recursive methods for solving the support vector machine regression problems

International journal of robust and nonlinear control, 2021-10, Vol.31 (15), p.7239-7260

2021

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Auxiliary model‐based iterative parameter estimation for a nonlinear output‐error system with saturation and dead‐zone nonlinearity

International journal of robust and nonlinear control, 2021-06, Vol.31 (9), p.4262-4286

2021

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Two‐stage recursive identification algorithms for a class of nonlinear time series models with colored noise

International journal of robust and nonlinear control, 2020-11, Vol.30 (17), p.7766-7782

2020

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Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements

Optimal control applications & methods, 2023-01, Vol.44 (1), p.243-258

2023

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Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems

Optimal control applications & methods, 2022-03, Vol.43 (2), p.402-417

2022

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Recursive methods for estimating the radial basis function‐based state‐dependent autoregressive model

International journal of robust and nonlinear control, 2020-04, Vol.30 (6), p.2475-2492

2020

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Adaptive filtering‐based multi‐innovation gradient algorithm for input nonlinear systems with autoregressive noise

International journal of adaptive control and signal processing, 2017-10, Vol.31 (10), p.1388-1400

2017

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On some parameter estimation algorithms for the nonlinear exponential autoregressive model

International journal of adaptive control and signal processing, 2019-06, Vol.33 (6), p.999-1015

2019

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Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data

Journal of computational and applied mathematics, 2023-07, Vol.426, p.115107, Article 115107

Ding, Feng

2023

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Two-stage Gradient-based Iterative Estimation Methods for Controlled Autoregressive Systems Using the Measurement Data

International Journal of Control, 2020, Automation, and Systems, 18(4), , pp.886-896

2020

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Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise

Journal of computational and applied mathematics, 2023-03, Vol.420, p.114794, Article 114794

2023

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Filtered auxiliary model recursive generalized extended parameter estimation methods for Box–Jenkins systems by means of the filtering identification idea

An efficient recursive identification algorithm for multilinear systems based on tensor decomposition

A novel nonlinear optimization method for fitting a noisy Gaussian activation function

The innovation algorithms for multivariable state‐space models

Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory

Auxiliary model‐based multi‐innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity

Multi‐innovation gradient‐based iterative identification methods for feedback nonlinear systems by using the decomposition technique

Filtered generalized iterative parameter identification for equation‐error autoregressive models based on the filtering identification idea

Hierarchical iterative identification algorithms for a nonlinear system with dead‐zone and saturation nonlinearity based on the auxiliary model

Auxiliary model‐based recursive least squares algorithm for two‐input single‐output Hammerstein output‐error moving average systems by using the hierarchical identification principle

Data filtering based multi‐innovation gradient identification for bilinear systems with colored noise

Three‐stage multi‐innovation parameter estimation for an exponential autoregressive time‐series model with moving average noise by using the data filtering technique

Identification of the nonlinear systems based on the kernel functions

The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise

Multi‐innovation Newton recursive methods for solving the support vector machine regression problems

Auxiliary model‐based iterative parameter estimation for a nonlinear output‐error system with saturation and dead‐zone nonlinearity

Two‐stage recursive identification algorithms for a class of nonlinear time series models with colored noise

Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements

Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems

Recursive methods for estimating the radial basis function‐based state‐dependent autoregressive model

Adaptive filtering‐based multi‐innovation gradient algorithm for input nonlinear systems with autoregressive noise

On some parameter estimation algorithms for the nonlinear exponential autoregressive model

Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data

Two-stage Gradient-based Iterative Estimation Methods for Controlled Autoregressive Systems Using the Measurement Data

Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise

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