An alternative method to zero-padded DFT

Donciu, Codrin; Temneanu, Marinel

doi:10.1016/j.measurement.2015.03.015

Cited by 17 publications

(7 citation statements)

References 13 publications

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“…frequency evaluation is possible [3]. A faster algorithm than zero-padded FFT is presented in [4]. The attained results are similar with those resulted by as zero-padding, but the computational effort is essentially reduced.…”

Section: Introductionmentioning

confidence: 67%

Early observation of modal parameter changes by an enhanced frequency evaluation algorithm

et al. 2016

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Abstract. By monitoring the vibration response of mechanical or civil engineering systems, the modal parameter changes due to materials or geometrical properties can be observed. Fine frequency shift identification is decisive to determine particularly small changes and thereby small cracks or damages. This paper firstly presents some existing methods to accurately find the frequency values. All these methods show non-linear, relevant errors in interpretation. Afterward a simple method is proposed, consisting in iterative decreasing of the number of samples from the original signal, performing a standard frequency analysis for each truncated signal and finally overlapping of achieved spectra. Thus, the resulted spectrum has a much fine resolution due to the important addition of spectral lines. In this way a more accurate identification of frequencies is possible. In fact, the relevant frequency is accomplished under a lobe shape. In the peak position of this lobe the best frequency value can be clearly identified. With the help of these more accurate frequency values, modal analysis becomes more reliable and efficient.

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Section: Introductionmentioning

confidence: 67%

Early observation of modal parameter changes by an enhanced frequency evaluation algorithm

et al. 2016

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“…The t-SVD Algorithm 2 adopted by TensorSSA is a tensor decomposition method based on discrete Fourier transform (DFT), and it may not be enough to directly apply DFT in signal processing and image processing. Therefore, zero padding [18] and [2] is needed to obtain accurate results, otherwise artifacts may occur. In our method, to obtain more accurate results, we need to add zero to the trajectory tensor, which will lead to a larger size of the third module.…”

Section: Algorithm 2 Truncated T-svdmentioning

confidence: 99%

An Effective Randomized Algorithm for Hyperspectral Image Feature Extraction

Feng,

Yan,

et al. 2024

Stat., optim. inf. comput.

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Analyzing the spectral and spatial characteristics of Hyperspectral Imaging (HSI) in a three-dimensional space is a challenging task. Recently, there have been developments in 3D feature extraction methods based on tensor decomposition, which allow for the effective utilization of both global and local information in HSI. These methods also explore the inherent low-rank properties of HSI through tensor decomposition. In this paper, we propose a new approach called variable randomized T-product decomposition (Vrt-SVD), which is a variation of Tensor Singular Spectral Analysis. The goal of this approach is to improve the efficiency of tensor methods for feature extraction and reduce artifacts of image processing. By using a randomized algorithm based on the variable t-SVD, we are able to capture both global and local spatial and spectral information in HSI efficiently, which enables us to explore its low-rank characteristics. To evaluate the effectiveness of the extracted features, we use a Support Vector Machine (SVM) classifier to assess the accuracy of image classification. By conducting numerous numerical experiments, we provide strong evidence to show that the proposed method outperforms several advanced feature extraction techniques.

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“…This method can achieve very good performance in frequency estimation with high SNR, but has poor noise immunity and requires iterative estimation with multiple times. Furthermore, to reduce the computational requirement and also achieve a good frequency resolution, the non-integer arguments for DFT evaluation is applied in [12], the chirp z-transform (CZT) is applied in [13,14] and the zoom interpolated DFT is employed in [15]. Nevertheless, these DFT-based techniques usually aim at reducing the picket fence effect and apply the peak searching method to achieve the beat frequency, but there exists some inherent limitations such as spectral leakage and noise sensitivity for high-precision frequency extraction.…”

Section: Measurement Science and Technologymentioning

confidence: 99%

High-precision frequency estimation for FMCW radar applications based on parameterized de-alternating and modified ICCD

Xiong

Chen

Xing

et al. 2018

Meas. Sci. Technol.

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In this paper, aiming to achieve high-resolution frequency estimation for frequency-modulated continuous wave (FMCW) radar applications, a novel frequency estimation algorithm based on parameterized de-alternating (PDA) is proposed. According to the beat signal model, the proposed PDA method is performed with a matched kernel function to achieve the best de-alternating performance (i.e. the maximum conversion from an oscillating signal to a constant signal). The kernel parameter is estimated by solving an optimization problem which is simple and computationally efficient. Moreover, for a multiple target scenario, the intrinsic chirp component decomposition (ICCD) method is employed to isolate different components of the beat signal, which can eliminate the mutual interference between adjacent components when performing the PDA method. Compared with the commonly used FFT technique, our method can greatly improve the frequency estimation resolution and achieve superior ranging performance with a limited bandwidth. Both simulated and experimental validations are provided to show the effectiveness of the proposed methods.

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An alternative method to zero-padded DFT

Cited by 17 publications

References 13 publications

Early observation of modal parameter changes by an enhanced frequency evaluation algorithm

Early observation of modal parameter changes by an enhanced frequency evaluation algorithm

An Effective Randomized Algorithm for Hyperspectral Image Feature Extraction

High-precision frequency estimation for FMCW radar applications based on parameterized de-alternating and modified ICCD

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