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 p
Robust complex non-linear regression method for the estimation of equivalent circuit parameters of the thickness-shear-mode acoustic wave sensor
β Scribed by Huwei Tan; Xiaoli Su; Wanzhi Wei; Shouzhuo Yao
- Publisher
- Elsevier Science
- Year
- 1999
- Tongue
- English
- Weight
- 433 KB
- Volume
- 48
- Category
- Article
- ISSN
- 0169-7439
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β¦ Synopsis
Fluctuation in characteristic parameters of the equivalent circuit for the thickness-shear-mode TSM acoustic wave sensor is a troublesome problem encountered in their practical applications. It is due to interference from normal and non-normal noise of an impedance analyzer. A robust complex non-linear regression, called complex least trimmed squares regres-Ε½ . sion CLTSR , is described and utilized in the parameter estimation to alleviate the fluctuation in this article. The results for simulated data indicated that, when the noise distribution was not normal, the CLTSR yields the more robust results than the Ε½ . ordinary complex least squares regression OCLSR , when the noise distribution was normal, almost the same estimates can be achieved with these two regression methods. The results for the real data indicated that, the noise in experiment could not be regarded as normal distribution. The CLTSR can eliminate the system error and alleviate the parameter fluctuation, especially fluctuation in L and C . The robust method, therefore, provides a safe alternative to OCLSR and other widely used m m methods.
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Wavelet packet denoising robust regression applied to estimation of equivalent circuit parameters for thickness-shear-mode acoustic wave sensor