Identification of MIMO systems using radial basis function networks with hybrid learning algorithm

DOI10.1016/J.AMC.2009.02.058zbMath1163.93326OpenAlexW1964514379MaRDI QIDQ1030231

Chia-Nan Ko, Jin-Tsong Jeng, Yu-Yi Fu, Chia-Ju Wu

Publication date: 1 July 2009

Published in: Applied Mathematics and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.amc.2009.02.058

zbMATH Keywords

system identificationMIMO systemradial basis function networkssupport vector regressionannealing robust learning algorithm

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Neural networks for/in biological studies, artificial life and related topics (92B20) System identification (93B30) Multivariable systems, multidimensional control systems (93C35)

Related Items (3)

WSVR-based fuzzy neural network with annealing robust algorithm for system identification ⋮ Hierarchical least squares based iterative estimation algorithm for multivariable Box-Jenkins-like systems using the auxiliary model ⋮ Reinforcement radial basis function neural networks with an adaptive annealing learning algorithm

Cites Work

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• A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts
• Identification of acoustic MIMO systems: challenges and opportunities
• On-line RBFNN based identification of rapidly time-varying nonlinear systems with optimal structure-adaptation.
• Convergence of HLS estimation algorithms for multivariable ARX-like systems

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