DocumentCode :
3056467
Title :
Parallel identifiers for parameter estimation of strongly disturbed ARMA-processes
Author :
Schurk, H.-E. ; Appel, U. ; Wolf, W.
Author_Institution :
Bundeswehr University, Munich, Neubiberg, FRG
Volume :
7
fYear :
1982
fDate :
30072
Firstpage :
262
Lastpage :
265
Abstract :
Several output error (or parallel) identifiers for parametric identification of discrete time autoregressive, moving-average (ARMA) systems with low signal-to-noise ratio were studied. An additional identification difficulty thereby was the estimation from a few number of data. Two kinds of adaptive recursive methods - model reference adaptive system algorithms (M.R.A.S.) and hyperstable adaptive recursive identifiers (HARF, e.g.) - were tested in simulation runs. The results are compared with an off-line (iterative) output error method and discussed. As a special case study modelling of human electroencephalogram (EEG) data is presented.
Keywords :
Adaptive systems; Brain modeling; Computer errors; Electroencephalography; Humans; Iterative algorithms; Iterative methods; Parameter estimation; Signal to noise ratio; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '82.
Type :
conf
DOI :
10.1109/ICASSP.1982.1171736
Filename :
1171736
Link To Document :
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