Title :
A modified identification algorithm for linear systems with noisy input-output data
Author_Institution :
Sch. of Quantitative Methods & Math. Sci., Univ. of Western Sydney, Penrith South, NSW, Australia
Abstract :
In this paper a modified identification algorithm for linear systems with noisy input-output data is developed. The main idea is to introduce extra equations so that the variances of the input noise and the output noise, which determine the noise-induced bias in the least-squares parameter estimator, can be estimated in a more accurate and quicker way. Due to this, such performance as estimation accuracy and convergence speed of the bias-correction based algorithm can be significantly boosted, at the expense of a fractional increase in the numerical cost. Computer simulations are presented, which leads to some useful conclusions.
Keywords :
convergence of numerical methods; identification; least squares approximations; linear systems; parameter estimation; BELS-AE algorithm; bias correction; computer simulation; convergence speed; identification algorithm; least squares parameter estimation; linear system; noisy input-output data; numerical method; variance; Application software; Australia; Computer simulation; Convergence of numerical methods; Costs; Equations; Linear systems; Parameter estimation; Signal processing algorithms; Signal to noise ratio;
Conference_Titel :
Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium on
Print_ISBN :
0-7803-7448-7
DOI :
10.1109/ISCAS.2002.1010269
