Comparison of two construction algorithms for local model networks

DOI10.1080/0020772021000046243zbMath1018.93502OpenAlexW2166670382MaRDI QIDQ4808248

Shaun McGinnity, Seamus Cornelius McLoone, George W. Irwin

Publication date: 10 September 2003

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/0020772021000046243

Mathematics Subject Classification ID

System identification (93B30)

Cites Work

• Unnamed Item
• Multivariate adaptive regression splines
• Stability analysis and design of fuzzy control systems
• Identification of nonlinear system structure and parameters using regime decomposition
• ASMO—Dan algorithm for adaptive spline modelling of observation data
• Fuzzy identification of systems and its applications to modeling and control
• Construction of composite models from observed data
• Frequency domain synthesis of trajectory learning controllers for robot manipulators
• Application of a general multi-model approach for identification of highly nonlinear processes-a case study
• Extended model set, global data and threshold model identification of severely non-linear systems
• Constructing NARMAX models using ARMAX models
• Analytic framework for blended multiple model systems using linear local models
• Piecewise linear identification of non-linear systems

This page was built for publication: Comparison of two construction algorithms for local model networks