General Parameterized Time-Frequency Transform

Yang, Yixin; Peng, Zhike; Dong, Xingjian; Zhang, W. M.; Meng, Guang

doi:10.1109/tsp.2014.2314061

Cited by 171 publications

(38 citation statements)

References 39 publications

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“…For the frequency estimation of the signal, the commonly used methods include peak detection, Short Time Fourier Transform (STFT) [17], Wavelet Transform (WT) [18], Wigner-Ville Distribution (WVD) [19], Hilbert-Huang Transform (HHT) [20], Chirp Transform (CT) [21], Polynomial Chirp Transform (PCT) [22], Zoom FFT [23], and Chirp-Z Transform (CZT) [24]. Among them, the peak detection method calculates the signal period by detecting the peak value of the signal, thereby obtaining the frequency of the signal.…”

Section: The Time-frequency Analysis Methods For Roll Angular Rate Estmentioning

confidence: 99%

Extraction and Filter Algorithm of Roll Angular Rate for High Spinning Projectiles

Zhao

Liu

et al. 2019

Mathematical Problems in Engineering

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The accurate measurement of roll angular rate for high spinning projectile has long been a challenging problem. Aiming to obtain the accurate roll angular rate of high spinning projectile, a novel extraction and filter algorithm, BSCZT-KF, is proposed in this paper. Firstly, a compound angular motion model of high spinning projectile is established. According to the model, we translate the roll angular rate measurement problem into a frequency estimation problem. Then the improved CZT algorithm, BSCZT, was employed to realize an accurate estimation of the narrowband signal frequency. Combined with the peak detection method, the BSCZT-KF algorithm is presented to further enhance the frequency estimation accuracy and the real-time performance. Finally, two sets of actual flight tests were conducted to verify the effectiveness and accuracy of the algorithm. The test results show that the average error of estimated roll angular rate is about 0.095% of the maximum of roll angular rate. Compared with the existing methods, the BSCZT-KF has the highest frequency estimation accuracy for narrowband signal.

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Section: The Time-frequency Analysis Methods For Roll Angular Rate Estmentioning

confidence: 99%

Extraction and Filter Algorithm of Roll Angular Rate for High Spinning Projectiles

Zhao

Liu

et al. 2019

Mathematical Problems in Engineering

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“…10 By replacing the chirplet kernel that has a linear IF law in the chirplet transform with a new kernel that has a polynomial nonlinear IF law, the PCT can generate a TFD that satisfies the energy concentration for the Doppler signal without the inner artifacts. The accurate estimation of the IF and its corresponding amplitude can be effectively achieved through a signal-dependent iterative procedure, the first iteration of which is the STFT.…”

Section: Introductionmentioning

confidence: 99%

Analysis of moving source characteristics using polynomial chirplet transform

Yang

2015

The Journal of the Acoustical Society of America

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The received Doppler signal of a stationary sensor, as emitted by a transiting acoustic source, is used to estimate source motion parameters, including speed, closest distance, rest frequency, and closest point of approach (CPA) time. First, the instantaneous frequency, amplitude, and CPA time are accurately estimated by the polynomial chirplet transform of the Doppler signal. Thereafter, the three other source motion parameters are obtained with a simplified amplitude-weighted nonlinear least squares method. The proposed scheme is successfully applied to the analysis of the characteristics of a moving truck.

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“…The standard spectrogram is easy to interpret. However, its performance depends on the analysis window that has been set heuristically and provides poor time or frequency resolution [34]. For example, Figure 1.4(c) plots the standard spectrogram of a multicomponent signal ( Figure 1.4(a)).…”

Section: Representing a Signal In The Time-frequency Domainmentioning

confidence: 99%

“…The optimal selection of these parameters offers a highly energy concentrated ( , ) representation with signal-dependant resolution [34]. But, how can we select these parameters for a multicomponent signal without a priori signal information?…”

Section: What Is Already Known On This Topic?mentioning

confidence: 99%

“…however, it suffers from cross-terms, potentially leading to confusion and misinterpretation of the signal components (due to the quadratic nature of the transform) ( The analysis window, window parameters and kernel parameters are often selected manually based on visual inspection (( [33], pp.93-94, 297-298), [34]). This is time consuming and not feasible in certain applications -for example, in automatic pattern recognition and classification [29].…”

Section: What Is Already Known On This Topic?mentioning

confidence: 99%

See 1 more Smart Citation

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

Awal¹

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Neonatal Hypoxic Ischaemic Encephalopathy (HIE) is a major cause of morbidity and mortality in newborns throughout the world with an incidence of 1-8/1000 newborns in developed countries and up to 26/1000 newborns in developing countries. It causes one million neonatal deaths globally per year. Electroencephalography (EEG) is a useful method for assessment of brain activity in newborns with HIE. EEG performs well in the early diagnosis and classification of HIE severity and in predicting neurodevelopmental outcome. A normal EEG is highly predictive of a normal outcome and various abnormal EEG features are associated with neurological abnormalities or death.A systematic review and meta-analysis of the literature was undertaken to determine which specific background features of the EEG best predict outcome (Aim 1). Automatic detection and classification

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General Parameterized Time-Frequency Transform

Cited by 171 publications

References 39 publications

Extraction and Filter Algorithm of Roll Angular Rate for High Spinning Projectiles

Extraction and Filter Algorithm of Roll Angular Rate for High Spinning Projectiles

Analysis of moving source characteristics using polynomial chirplet transform

Design and optimisation of time-frequency analysis for multichannel neonatal EEG background features in term neonates with hypoxic ischaemic encephalopathy: characterisation, classification and neurodevelopmental outcome prediction

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