Finite sample properties of system identification with quantized output data
Erik Weyer, Sangho Ko, Marco C Campi
PROCEEDINGS OF THE 48TH IEEE CONFERENCE ON DECISION AND CONTROL, 2009 HELD JOINTLY WITH THE 2009 28TH CHINESE CONTROL CONFERENCE (CDC/CCC 2009) | IEEE | Published : 2009
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. ©2009 IEEE.
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Awarded by Australian Research Council
The work of E. Weyer was supported by the Australian Research Council under Discovery Grant DP0558579.