Finite sample properties of system identification with quantized output data

Author

Weyer, Erik ; Ko, Sangho ; Campi, Marco C.

Author_Institution

Dept. of Electr. & Electron. Eng., Univ. of Melbourne, Parkville, VIC, Australia

fYear

2009

fDate

15-18 Dec. 2009

Firstpage

1532

Lastpage

1537

Abstract

In this paper, we consider system identification with quantized output data. We show that by applying an LSCR (leave-out sign-dominant correlation regions) algorithm guaranteed non-asymptotic confidence sets for the system parameters can be obtained. The results and the confidence sets are valid for any finite number of data points, and there are no assumptions on the noise. Simulation examples are provided which illustrate the usefulness of the algorithm and which also point to open research problems in quantizer and input signal design.

Keywords

correlation methods; quantisation (signal); finite sample property; leave-out sign-dominant correlation region algorithm; nonasymptotic confidence set; quantized output data; system identification; Australia Council; Networked control systems; Noise measurement; Q measurement; Quantization; Sensor phenomena and characterization; Signal design; Signal processing; System identification; Wireless sensor networks;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on

Conference_Location

Shanghai

ISSN

0191-2216

Print_ISBN

978-1-4244-3871-6

Electronic_ISBN

0191-2216

Type

conf

DOI

10.1109/CDC.2009.5399796

Filename

5399796