2013
DOI: 10.4236/am.2013.411a3003
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Comparison between Fourier and Wavelets Transforms in Biospeckle Signals

Abstract: The dynamic speckle is a non-destructive optical technique that has been used as a tool for the characterization of the biological activity and several studies are conducted to obtain for more information about the correspondence of the observed phenomena and their expressions in the interference images. Analysis in the frequency domain has been considered as powerful alternative, and although there are works using Fourier transform in the frequency analysis of the biospeckle signals, the majority presents the… Show more

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Cited by 13 publications
(4 citation statements)
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“…Various methods like Short Time window Fourier Transform (STFT), Wavelet Transform, S-Transform (ST), Matching Pursuit Decomposition (MPD), and Empirical Mode Decomposition are employed for this purpose. Therefore, it is important to consider the strengths and limitations of these methods for effective subsurface geological feature delineation [12] [13] [14].…”
Section: Fourier and Wavelet Transformmentioning
confidence: 99%
See 1 more Smart Citation
“…Various methods like Short Time window Fourier Transform (STFT), Wavelet Transform, S-Transform (ST), Matching Pursuit Decomposition (MPD), and Empirical Mode Decomposition are employed for this purpose. Therefore, it is important to consider the strengths and limitations of these methods for effective subsurface geological feature delineation [12] [13] [14].…”
Section: Fourier and Wavelet Transformmentioning
confidence: 99%
“…Its significance lies in the ability to identify the dominant frequency components associated with subsurface geological features. This makes it particularly valuable for processing large amounts of data and characterizing complex structures [14] [15] [16].…”
Section: Fourier and Wavelet Transformmentioning
confidence: 99%
“…3 Foundation of NMF Among the wide variety of sound separation algorithms, the unsupervised Non-negative Matrix Factorization (NMF) dictionary learning algorithm suits well for the delineation of sound mixture [28,29]. The Cost function of Non-negative Matrix Factorization (NMF) will decompose their spectrogram into two non-negative matrices such as; a dictionary matrix W f d and a coefficient matrix Hdt.…”
Section: Tree Structured Wavelet Filter Bankmentioning
confidence: 99%
“…Instead of using PSD, the Shannon Entropy can also be applied to the decomposition of the signal using the DWTE 21,22,23,24 . DWTE makes no assumptions about signal stationary feature 7 , so it provides a useful tool for the frequency analysis considering the temporal location 23 .…”
Section: Discrete Wavelet Transform Entropy (Dwte)mentioning
confidence: 99%