On‐line system identification of structures using wavelet‐Hilbert transform and sparse component analysis

2020 ◽  
Vol 35 (8) ◽  
pp. 870-886 ◽  
Author(s):  
Kaveh Karami ◽  
Pejman Fatehi ◽  
Azad Yazdani
Keyword(s):  
System Identification ◽  
Hilbert Transform ◽  
Component Analysis ◽  
Line System ◽  
Sparse Component Analysis ◽  
On Line

Analog methods for on-line system identification using noisy measurements

SIMULATION ◽  
1968 ◽  
Vol 11 (5) ◽  
pp. 241-248 ◽  
Author(s):  
D.W. Ricker ◽  
G.N. Saridis
Keyword(s):  
System Identification ◽  
Nonlinear Systems ◽  
Automatic Control ◽  
Stochastic Approximation ◽  
Linear Time ◽  
Measurement Noise ◽  
Current Interest ◽  
Line System ◽  
On Line ◽  
Noisy Measurements

Of current interest in the field of automatic control is the problem of system identification in the presence of measurement noise. Generally this problem has been dis cussed in the literature for the case of linear time-invar iant systems where the parameters to be identified are constant or slowly varying. This paper describes the ap plication of continuous stochastic approximation meth ods for the identification of a class of simple nonlinear systems. The two algorithms described are easily imple mented with analog equipment, although one of them requires some logic capability.

On-line system identification with an adjustable estimation interval

1988 ◽  
Vol 19 (10) ◽  
pp. 1955-1967 ◽  
Author(s):  
WEN-TENG WU ◽  
WEI-HSIUNG OU ◽  
KUO-CHIEH CHEN
Keyword(s):  
System Identification ◽  
Line System ◽  
On Line ◽  
Estimation Interval
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