Identification of nonlinear system structure and parameters using regime decomposition

DOI10.1016/0005-1098(94)00096-2zbMath0825.93114OpenAlexW2090013042WikidataQ127294082 ScholiaQ127294082MaRDI QIDQ1891001

Yanyan Li

Publication date: 28 November 1995

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0005-1098(94)00096-2

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Geometric methods (93B27)

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Cites Work

• On covariance function tests used in system identification
• Structure identification of fuzzy model
• Multivariate adaptive regression splines
• Fitting autoregressive models for prediction
• ASMO—Dan algorithm for adaptive spline modelling of observation data
• Fuzzy identification of systems and its applications to modeling and control
• Model-structure selection by cross-validation
• Construction of composite models from observed data
• Application of a general multi-model approach for identification of highly nonlinear processes-a case study
• Constructing NARMAX models using ARMAX models
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