Recursive least mean dual p-power solution to the generalization of evolving fuzzy system under multiple noises

DOI10.1016/J.INS.2022.07.090OpenAlexW4286256894MaRDI QIDQ6122195

Zhaoxu Yang, Unnamed Author, Chi-Man Vong, Hai-Jun Rong

Publication date: 27 March 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2022.07.090

zbMATH Keywords

stabilitynon-Gaussian noisesevolving fuzzy systemrecursive least mean dual \(p\)-power

Mathematics Subject Classification ID

Computer science (68-XX) Systems theory; control (93-XX)

Cites Work

• Maximum correntropy Kalman filter
• Evolving fuzzy classifiers using different model architectures
• \(L_ p\) normed minimization with applications to linear predictive modeling for sinusoidal frequency estimation
• Improving the robustness of recursive consequent parameters learning in evolving neuro-fuzzy systems
• Recursive least mean \(p\)-power extreme learning machine
• Sequential adaptive fuzzy inference system (SAFIS) for nonlinear system identification and prediction
• A new type of simplified fuzzy rule-based system
• Correntropy: Properties and Applications in Non-Gaussian Signal Processing
• Generalized Correntropy for Robust<?Pub _newline ?>Adaptive Filtering

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