Comprehensive Performance Evaluation of Computationally Efficient Discrete Fourier Transforms for Frequency Estimation

Tyagi, Tushar; Sumathi, P.

doi:10.1109/tim.2019.2922751

Cited by 23 publications

(9 citation statements)

References 27 publications

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“…W V = exp −k 2π V , and V denotes the length of change interval; f (k) denotes the original signal, and F( j) denotes discrete Fourier transform; k represents the interval length of Fourier transform. Further details can be found in [66][67][68][69].…”

Section: Fast Fourier Transform Methodsmentioning

confidence: 99%

An Adaptive Cutoff Frequency Selection Approach for Fast Fourier Transform Method and Its Application into Short-Term Traffic Flow Forecasting

Wang

Shi

Liu

et al. 2020

IJGI

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Historical measurements are usually used to build assimilation models in sequential data assimilation (S-DA) systems. However, they are always disturbed by local noises. Simultaneously, the accuracy of assimilation model construction and assimilation forecasting results will be affected. The fast Fourier transform (FFT) method can be used to acquire de-noised historical traffic flow measurements to reduce the influence of local noises on constructed assimilation models and improve the accuracy of assimilation results. In the practical signal de-noising applications, the FFT method is commonly used to de-noise the noisy signal with known noise frequency. However, knowing the noise frequency is difficult. Thus, a proper cutoff frequency should be chosen to separate high-frequency information caused by noises from the low-frequency part of useful signals under the unknown noise frequency. If the cutoff frequency is too high, too much noisy information will be treated as useful information. Conversely, if the cutoff frequency is too low, part of the useful information will be lost. To solve this problem, this paper proposes an adaptive cutoff frequency selection (A-CFS) method based on cross-validation. The proposed method can determine a proper cutoff frequency and ensure the quality of de-noised outputs for a given dataset using the FFT method without noise frequency information. Experimental results of real-world traffic flow data measurements in a sub-area of a highway near Birmingham, England, demonstrate the superior performance of the proposed A-CFS method in noisy information separation using the FFT method. The differences between true and predicted traffic flow values are evaluated using the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage (MAPE) values. Compared to the results of the two commonly used de-noising methods, i.e., discrete wavelet transform (DWT) and ensemble empirical mode decomposition (EEMD) methods, the short-term traffic flow forecasting results of the proposed A-CFS method are much more reliable. In terms of the MAE value, the average relative improvements of the assimilation model built using the proposed method are 19.26%, 3.47%, and 4.25%, compared to the model built using raw data, DWT method, and EEMD method, respectively; the corresponding average relative improvements in RMSE are 19.05%, 5.36%, and 3.02%, respectively; lastly, the corresponding average relative improvements in MAPE are 18.88%, 2.83%, and 2.28%, respectively. The test results show that the proposed method is effective in separating noises from historical measurements and can improve the accuracy of assimilation model construction and assimilation forecasting results.

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Section: Fast Fourier Transform Methodsmentioning

confidence: 99%

An Adaptive Cutoff Frequency Selection Approach for Fast Fourier Transform Method and Its Application into Short-Term Traffic Flow Forecasting

Wang

Shi

Liu

et al. 2020

IJGI

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“…Besides, deep comparisons between different frequency‐domain methods, such as DFT, HDFT, SDFT and mHSDFT have been taken in Ref. [21]. In Ref.…”

Section: Introductionmentioning

confidence: 99%

Model Predictive Current Control for the Grid‐Connecting Three‐Level NPC Inverters Based on an Effective Harmonic Extraction Method Under a Low‐Switching Frequency

Hou

Tan

2022

IEEJ Transactions Elec Engng

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Current control of the grid-connecting inverters usually has an important influence on the control performance especially when the inverters operate at a low-switching frequency for it would result in a severe harmonic distortion in the output current components. To improve the current control performance, a novel model predictive current control (MPCC) strategy based on an effective harmonic extraction method was present for a high-power three-level NPC inverter in this paper. First, an effective amplitudes extraction method called generalized sliding discrete Fourier transform (GSDFT) was designed for the fundamental and low-order harmonic current components, and which would be taken as a part of the cost function for the MPCC besides the consideration of switch losses and neutral point potential balancing issues. Experimental results verify that this kind of novel control strategy not only has a characteristic similar with the selective harmonic elimination, also could realize a nice current control performance even the switching frequency is low than 500 Hz as well as a neutral point potential balancing.

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“…Several applications have been published recently where such algorithms can be employed efficiently. An efficient method using SDFT was proposed for frequency estimation [1] and tone detection [2]. For synchronization purposes, such an application was given in [3].…”

Section: Introductionmentioning

confidence: 99%

FPGA Realization of the Observer-Based Sliding Discrete Fourier Transform

2022

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Discrete Fourier transform (DFT) is a widely used method of signal analysis in digital signal processing. The DFT converts a signal from time domain to frequency domain for further processing. For fixed-size sliding window applications of the DFT, the observer-based sliding DFT (oSDFT) algorithm has been shown to be stable, accurate, and theoretically faster, than the well-known block-oriented fast Fourier transforms (FFT). However, no hardware implementation of the oSDFT has been proposed yet. In this paper, a hardware optimized implementation of two variants of the algorithm for FPGA is presented. Such implementation is compared with the Xilinx FFT Intellectual Property in terms of processing speed and hardware requirements. The structure is implemented in Verilog HDL using Vivado IDE, with the aim of maximizing the processing speed and minimizing the required hardware resources. The analysis of the FPGA-based oSDFT and FFT circuits in a sample-by-sample processing scenario, reveals, that the latency and energy usage of the oSDFT are smaller relative to the FFT. The latency and energy usage per sample processed of the implemented structures are up to 9 and 10 times lower than those of FFT respectively. The required resources for these methods are also presented and analyzed.

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Comprehensive Performance Evaluation of Computationally Efficient Discrete Fourier Transforms for Frequency Estimation

Cited by 23 publications

References 27 publications

An Adaptive Cutoff Frequency Selection Approach for Fast Fourier Transform Method and Its Application into Short-Term Traffic Flow Forecasting

An Adaptive Cutoff Frequency Selection Approach for Fast Fourier Transform Method and Its Application into Short-Term Traffic Flow Forecasting

Model Predictive Current Control for the Grid‐Connecting Three‐Level NPC Inverters Based on an Effective Harmonic Extraction Method Under a Low‐Switching Frequency

FPGA Realization of the Observer-Based Sliding Discrete Fourier Transform

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