The Effects of Noise on Frequency-Domain Parameter Estimation of Synchronous Machine Models
β Scribed by Keyhani, A.; Hao, S.; Dayal, G.
- Book ID
- 117900438
- Publisher
- IEEE
- Year
- 1989
- Tongue
- English
- Weight
- 416 KB
- Volume
- 9
- Category
- Article
- ISSN
- 0272-1724
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This paper is dealing with high power broadband signals (multisines) applied in Stand-Still Frequency Response (SSFR) technique for the measuring and modelling of electrical machine characteristics. The powerful excitation signals used are periodic functions with controllable amplitude spectrum. The
The structure of noise in a dataset and, in particular, whether it is homoscedastic or heteroscedastic, can significantly affect the properties of multivariate calibration models. This is particularly true when the data are subjected to a nonlinear transformation prior to the formation of the model.