Adaptive dynamic TSKCMAC neural networks for prediction and identification

In this paper, a dynamic Takagi-Sugeno-Kang type cerebellar model articulation controller (TSKCMAC) neural network is developed for solving the prediction and identification problem. A dynamic TSKCMAC is combines both the merits of TSK fuzzy model and conventional cerebellar model articulation contr...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Yu-Lin Liao, Ya-Fu Peng, Chiung-Chou Liao
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Aerospace electronics Convergence Feedforward neural networks identification Lyapunov methods prediction Simulation Takagi-Sugeno model Takagi-Sugeno-Kang type TSKCMAC
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