Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory-Reference-Cited by-同舟云学术

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

Published:2022-06-14 Issue:13 Volume:32 Page:7304-7318
ISSN:1049-8923
Container-title:International Journal of Robust and Nonlinear Control
language:en
Short-container-title:Intl J Robust & Nonlinear

Author:

Wang Yanjiao¹^ORCID,Tang Shihua¹^ORCID,Deng Muqing¹

Affiliation:

1. School of Automation Guangdong University of Technology Guangzhou China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Mechanical Engineering,Aerospace Engineering,Biomedical Engineering,General Chemical Engineering,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rnc.6221

Reference78 articles.

1. Perspectives on system identification

2. Separable Multi-innovation Newton Iterative Modeling Algorithm for Multi-frequency Signals Based on the Sliding Measurement Window

3. Separable Newton Recursive Estimation Method Through System Responses Based on Dynamically Discrete Measurements with Increasing Data Length

4. Applying polynomial decoupling methods to the polynomial NARX model

5. Nonlinear system identification of a MIMO quadruple tanks system using NARX model;Araujo I;Prz Elektrotechniczny,2019

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