Time-Frequency Analysis

Girón-Sierra, José M.

doi:10.1007/978-981-10-2534-1_7

Cited by 2 publications

(2 citation statements)

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“…In signal processing, time-frequency (TF) analysis [9] concerns with methods to study the signal in both the time and frequency domains simultaneously, using various TF representations (distributions) when dealing with signal whose spectral content is time-varying. In general, these methods are refinement of Fourier analysis [11] for the case when the signal frequency characteristics are varying with time such as speech, images, and medical signals.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

“…For example, the sunspot time series [8] counts the average number of sunspots every year and is illustrated in Figure 1 (b) which shows yearly sunspot numbers during the period from 1700 to 2018. Primarily, this work provides an essential investigation and discussion for two popular Time-Frequency (TF) Analysis [9] techniques to develop a joint function of time and frequency, known as a time-frequency distribution [10], that can describe the energy density of a signal simultaneously in both time and frequency. Specifically, the main contributions of this paper can be summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

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A Methodical Study for Time-Frequency Analysis Model with Experimental Case Study on Chirp Signal

Al‐Haija¹

2020

IJEM

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In this paper, we are reporting on the comprehensive model design for time-frequency analysis system using Short-Time Fourier Transform (STFT) and Wigner-Ville Distribution (WVD) methods. As a case study, both STFT and WVD based time-frequency transforms have been developed via MATLAB platform and applied for both Chirp and Sunspot signals. The developed model considers the use of hamming moving window of length L=50 with 90% overlapping between the current and previous window positions. The simulation results showed that WVD is more accurate method for time and frequency analysis than STFT since it can provide simultaneous localization in both time and frequency with higher resolution than STFT which can only provide localization in either time or frequency at the same time. Also, the applied techniques provide an adequate distribution of time-frequency analysis only if they used with a non-stationary signal such as Chirp signal.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%