Identification of nonlinear discrete-time systems using raised-cosine radial basis function networks

DOI10.1080/00207720410001703213zbMath1060.93033OpenAlexW2069152951MaRDI QIDQ4828701

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Publication date: 26 November 2004

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

Full work available at URL: https://doi.org/10.1080/00207720410001703213

zbMATH Keywords

system identificationnonlinear discrete-time systemssaturationraised cosine radial basis function networks

Mathematics Subject Classification ID

System identification (93B30) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55)

Cites Work

• Adaptive radial basis function neural network control with variable variance parameters
• Synthesis of the sliding-mode neural network controller for unknown nonlinear discrete-time systems
• Non-linear system identification using neural networks
• Recursive hybrid algorithm for non-linear system identification using radial basis function networks
• Neural networks for nonlinear dynamic system modelling and identification
• Identification of time-varying nonlinear systems using minimal radial basis function neural networks
• Neural network-based variable structure control for nonlinear discrete systems
• Stability of nonlinear polynomial ARMA models and their inverse
• Sequential Exploration of Unknown Multi-dimensional Functions as an Aid to Optimization

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