Wavelet packet denoising robust regression applied to estimation of equivalent circuit parameters for thickness-shear-mode acoustic wave sensor

✍ Scribed by Hu-Wei Tan

• Publisher: John Wiley and Sons
• Year: 1999
• Tongue: English
• Weight: 107 KB
• Volume: 13
• Category: Article
• ISSN: 0886-9383
• DOI: 10.1002/(sici)1099-128x(199911/12)13:6<543::aid-cem561>3.0.co;2-v

✦ Synopsis

Fluctuation in characteristic parameters of the equivalent circuit for a thickness-shear-mode (TSM) acoustic wave sensor is a troublesome problem encountered in their practical applications. This fluctuation is due to interference from normal and non-normal noise of the impedance analyser. In this paper, a novel robust nonlinear fitting method, namely complex least trimmed squares regression via wavelet packet denoising (WPD-CLTSR), is proposed and utilized for robust parameter estimation to alleviate this fluctuation. The generalized simulated annealing (GSA) algorithm is adopted as an optimization procedure in the process of WPD-CLTSR to guarantee convergence to the global optimum. The results for both simulated and experimental data sets show a significant improvement in the fluctuation compared with a conventional least squares method and a robust regression method, i.e. the ordinary complex least squares regression (OCLSR) method and the complex least trimmed squares regression (CLTSR) method. Therefore the WPD-CLTSR method provides a safe alternative to the other widely used methods, no matter whether the noise is normal or non-normal.