Kernel Width Optimization for Faulty RBF Neural Networks with Multi-node Open Fault

Many researches have been devoted to select the kernel parameters, including the centers, kernel width and weights, for fault-free radial basis function (RBF) neural networks. However, most are concerned with the centers and weights identification, and fewer focus on the kernel width selection. More...

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Veröffentlicht in:	Neural processing letters 2010-08, Vol.32 (1), p.97-107
Hauptverfasser:	Wang, Hong-Jiang, Leung, Chi-Sing, Sum, Pui-Fai, Wei, Gang
Format:	Artikel
Sprache:	eng
Schlagworte:	Applied sciences Artificial Intelligence Complex Systems Computational Intelligence Computer Science Computer science control theory systems Connectionism. Neural networks Exact sciences and technology Neural networks Nodes Radial basis function
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