The Fast Fourier and Hilbert-Huang Transforms: A Comparison

Donnelly, Denis

doi:10.15837/ijccc.2006.4.2305

Cited by 26 publications

(17 citation statements)

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“…FFT provides an efficient algorithm for converting data from the time domain into the frequency domain ( [4]). However, the Discrete Fourier Transform (DFT) transforms discrete data from the time domain to frequency domain.…”

Section: Methodology Fourier Transformmentioning

confidence: 99%

Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

Ismail

Mamat

Hamzah³

et al. 2014

AIP Conference Proceedings

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Section: Methodology Fourier Transformmentioning

confidence: 99%

Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

Ismail

Mamat

Hamzah³

et al. 2014

AIP Conference Proceedings

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“…In other words, Fast Fourier transform is applicable only for linear and stationary data analysis. Moreover, the estimation of the frequency of this algorithm is sensitive to noise [13].…”

Section: Fast Fourier Transform (Fft)mentioning

confidence: 99%

Realtime implementation of an internal-model-principle signal identifier

Mohsen

Brown

2017

2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)

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This thesis presents a new means of tuning an adaptive internal model principle based signal identification algorithm whose computational costs are low enough to allow a realtime implementation.The algorithm allows an instantaneous Fourier decomposition of nonstationary signals that have a strongly predictable component. The algorithm is implemented as a feedback loop resulting in a closed loop system with a frequency response of a bandpass filter with notches at the frequencies of the Fourier decomposition. This is achieved through real time selection of the coefficients of the transfer functions in the feedback loop. Previous work showed how the dynamics of the algorithm could be chosen to be represented by a bandpass filter with notches. However this involved solving a large set of coupled linear equations. This thesis shows how the equations can be decoupled into pairs of linear equations which have explicit solutions. In other word, rules for explicitly solving for these parameters are given that only involve evaluating frequency responses at the frequencies of the instantaneous Fourier decomposition. Last but not the least, alternative approach for choosing suitable coefficients to eliminate the DC component of the signal under consideration has been proposed as well by changing frequency response of the closed loop system from bandpass filter to a lowpass filter and adding a model of the constant signal to the feedback loop.

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“…Having the signal decomposed into a set of IMFs, the Hilbert-Huang transform (HHT) can be formed using the Hilbert transform of each of the resulting modes and determining both the Hilbert transform magnitudes and the instantaneous frequencies of the corresponding IMFs [4,8,9]. The HHT is then the accumulation of the Hilbert transform amplitudes of all extracted IMFs at the same frequencies.…”

Section: Emd and Hilbert-huang Transformmentioning

confidence: 99%

Spectral investigations of intraluminal impedance signals

Al-Zaben

Al-Zaatreh

Alquran

2009

Journal of Medical Engineering & Technology

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In this paper, an investigation of the spectral characteristics of intraluminal impedance signals using local Hilbert-Huang transform is presented. The impedance waveform may contain three main events: reflux event, swallow event and baseline region corresponding to no activity. The three events are analysed using local Hilbert-Huang transform to characterize the frequency contents of each event. In addition to the results of the Hilbert-Huang transform a time domain description of each event is presented.

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The Fast Fourier and Hilbert-Huang Transforms: A Comparison

Cited by 26 publications

References 0 publications

Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

Forecasting performance of denoising signal by Wavelet and Fourier Transforms using SARIMA model

Realtime implementation of an internal-model-principle signal identifier

Spectral investigations of intraluminal impedance signals

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