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
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