DocumentCode :
2820011
Title :
System identification using quantized data
Author :
Agüero, Juan C. ; Goodwin, Graham C. ; Yuz, Juan I.
Author_Institution :
Univ. of Newcastle, Newcastle
fYear :
2007
fDate :
12-14 Dec. 2007
Firstpage :
4263
Lastpage :
4268
Abstract :
In this paper we consider the problem of identification of linear systems using quantized data. We argue that, where possible, it is desirable to not utilize "naively" quantized data but instead it is preferable to choose the quantization mechanism carefully. In particular, we show that using a generalized noise shaping coder improves the accuracy of the estimates. We examine the accuracy of estimates for both naive and coded quantizers.
Keywords :
linear systems; parameter estimation; quantisation (signal); white noise; coded quantizers; generalized noise shaping coder; linear system identification; naive quantizers; quantization mechanism; quantized data; white noise; Additive noise; Communication channels; Communication system control; Control systems; Linear systems; Noise shaping; Quantization; Signal processing; System identification; USA Councils;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2007 46th IEEE Conference on
Conference_Location :
New Orleans, LA
ISSN :
0191-2216
Print_ISBN :
978-1-4244-1497-0
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2007.4434350
Filename :
4434350
Link To Document :
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