A total least squares enhanced smart DFT technique for frequency estimation of unbalanced three-phase power systems

Li, Zhe

doi:10.1016/j.ijepes.2020.106722

Cited by 10 publications

(2 citation statements)

References 36 publications

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“…Here we default to the fact that parameter  is known and  is a positive definite matrix [17]. Therefore, the least squares estimate for parameter c  is:…”

Section: mentioning

confidence: 99%

Combined with linear regression analysis of Hainan coconut carving art dissemination path analysis

Qian,

Ye,

Cao

2023

Applied Mathematics and Nonlinear Sciences

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Hainan coconut carving is regarded as an excellent traditional cultural treasure of the Chinese nation, which has a long history with a long history, but the current dissemination of the art of Hainan coconut carving is faced with the dilemma of decline. This paper carries out the construction of a multiple linear regression model, using the least squares method to determine the regression parameters and find the maximum likelihood estimation of the regression parameters. Then, the relevant elements of the art communication path, based on the elements of the construction of the art communication of multiple linear regression model and the production of questionnaires used to obtain the art communication path influence factors data. The least squares and maximum likelihood parameter estimation are numerically simulated, and the art communication path is analyzed using multiple linear regression. The results show that the mean square error of the least squares method is below 0.001 when the sample size of maximum likelihood estimation is increased from 100 to 300, the error rate of different parameters is reduced by 70.83%, and the significance of the influencing factors in the multivariate linear regression model is less than 0.05. Based on the linear regression, we can analyze the influencing factors of the dissemination path of the art of Hainan Coconut Sculpture, which provides a reference to the further expansion of the art of Hainan Coconut Sculpture. It can provide a reference for further expanding the dissemination of Hainan coconut carving art.

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“…Here we default to the fact that parameter  is known and  is a positive definite matrix [17]. Therefore, the least squares estimate for parameter c  is:…”

Section: mentioning

confidence: 99%

Combined with linear regression analysis of Hainan coconut carving art dissemination path analysis

Qian,

Ye,

Cao

2023

Applied Mathematics and Nonlinear Sciences

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“…One-cycle, leakage-free frequency estimation can be obtained by the smart DFT (SDFT) [18][19][20][21] which gained popularity for P-class phasor estimation in electric power systems. The frequency in the SDFT is estimated based on three DFT bins, computed for three consecutive signal fragments selected by the rectangular observation window shifted by one sample.…”

Section: Introductionmentioning

confidence: 99%

Metrology and Measurement Systems

Duda,

Zieliński

2021

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A new solution to the problem of frequency estimation of a single sinusoid embedded in the white Gaussian noise is presented. It exploits, approximately, only one signal cycle, and is based on the well-known 2nd order autoregressive difference equation into which a downsampling is introduced. The proposed method is a generalization of the linear prediction based Prony method for the case of a single undamped sinusoid. It is shown that, thanks to the proposed downsampling in the linear prediction signal model, the overall variance of the least squares solution of frequency estimation is decreased, when compared to the Prony method, and locally it is even close to the Cramér-Rao Lower Bound, which is a significant improvement. The frequency estimation variance of the proposed solution is comparable with, computationally more complex, the Matrix Pencil and the Steiglitz-McBride methods. It is shown that application of the proposed downsampling to the popular smart DFT frequency estimation method also significantly reduces the method variance and makes it even better than the least squares smart DFT. The noise immunity of the proposed solution is achieved simultaneously with the reduction of computational complexity at the cost of narrowing the range of measured frequencies, i.e. a sinusoidal signal must be sufficiently oversampled to apply the proposed downsampling in the autoregressive model. The case of 64 samples per period with downsampling up to 16, i.e. 1/4th of the cycle, is presented in detail, but other sampling scenarios, from 16 to 512 samples per period, are considered as well.

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Recursive sliding DFT algorithms: A review

Chauhan

Singh

2022

Digital Signal Processing

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A total least squares enhanced smart DFT technique for frequency estimation of unbalanced three-phase power systems

Cited by 10 publications

References 36 publications

Combined with linear regression analysis of Hainan coconut carving art dissemination path analysis

Combined with linear regression analysis of Hainan coconut carving art dissemination path analysis

Metrology and Measurement Systems

Recursive sliding DFT algorithms: A review

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