Reduced kernel recursive least squares algorithm for aero-engine degradation prediction

•The novel method considers all the constraints generated by the whole training set.•The redundant data is used to modify the coefficients related to each kernel unit.•The structure update and coefficient adjustment are carried out independently.•A more compact network without accuracy deterioration...

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Vydané v:	Mechanical systems and signal processing Ročník 95; s. 446 - 467
Hlavní autori:	Zhou, Haowen, Huang, Jinquan, Lu, Feng
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Berlin Elsevier Ltd 01.10.2017 Elsevier BV
Predmet:	Accuracy Adaptive algorithms Adaptive filters Aero-engine Basis functions Degradation Kernel recursive least squares Least squares method Markov chains Mathematical models Prognostics Radial basis function Recursive algorithms Reduced technique Redundancy Remaining useful life Signal processing Sparse kernel method Time series Training Reduced technique Aero-engine Remaining useful life Kernel recursive least squares Prognostics Sparse kernel method
ISSN:	0888-3270, 1096-1216
On-line prístup:	Získať plný text
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