Title :
A Method of Noise Model Identification Based On M-Series
Author :
Huijun, Li ; Qigang, Wang ; Gang, Ji ; Zengliang, Ma
Author_Institution :
Chinese Acad. of Sci., Beijing
Abstract :
It is necessary that the signal-to-noise ratio of the measured output signals must be large enough when we use the methods of identification to establish the mathematical model of the system. If the power of the noise in the output signals is too large, the model established through system identification will not reflect the fact, and the controller based on the model will not get expectant effect. In this application, we need establish the model of noise, and preprocess the output signals according to the model. This paper provided a least-square method to identify the noise model using M series as the input signal of the noise model.
Keywords :
identification; least squares approximations; noise; signal processing; M-series; controller; least-square method; mathematical model; noise model identification; signal-to-noise ratio; system identification; Automation; Electronic mail; Least squares methods; Mathematical model; Noise measurement; Power system modeling; Signal processing; Signal to noise ratio; System identification; White noise; Least Square; M-Series; Noise; System Identification;
Conference_Titel :
Control Conference, 2007. CCC 2007. Chinese
Conference_Location :
Hunan
Print_ISBN :
978-7-81124-055-9
Electronic_ISBN :
978-7-900719-22-5
DOI :
10.1109/CHICC.2006.4346848
