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http://dx.doi.org/10.7776/ASK.2021.40.3.213

A study on robust recursive total least squares algorithm based on iterative Wiener filter method  

Lim, Jun Seok (Department of Electrical Engineering, Sejong University)
Publication Information
The Journal of the Acoustical Society of Korea / v.40, no.3, 2021 , pp. 213-218 More about this Journal
Abstract
It is known that total least-squares method shows better estimation performance than least-squares method when noise is present at the input and output at the same time. When total least squares method is applied to data with time series characteristics, Recursive Total Least Squares (RTS) algorithm has been proposed to improve the real-time performance. However, RTLS has numerical instability in calculating the inverse matrix. In this paper, we propose an algorithm for reducing numerical instability as well as having similar convergence to RTLS. For this algorithm, we propose a new RTLS using Iterative Wiener Filter (IWF). Through the simulation, it is shown that the convergence of the proposed algorithm is similar to that of the RTLS, and the numerical robustness is superior to the RTLS.
Keywords
Total least squares; Iterative Wiener Filter (IWF); Numerical robustness; Recursive algorithm;
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