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How do you do wavelet analysis in R? 

Discrete wavelet transform
Wavelet
Second-generation wavelet transform
Wavelet packet decomposition
Wavelet transform

Answers from top 18 papers

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Papers (18)Insight
Journal Article•DOI
Lifting scheme for biorthogonal multiwavelets originated from Hermite splines
Amir Averbuch, Valery A. Zheludev 
01 Mar 2002-IEEE Transactions on Signal Processing
21 Citations
We present new pre(post)-processing algorithms that do not degrade the approximation accuracy of the vector wavelet transforms.
Proceedings Article•DOI
Wavelet Denoising and Its Implementation in LabVIEW
Bingsheng Wu, Chaozhi Cai 
30 Oct 2009
Wavelet methods using denoising is an important aspect of wavelet analysis applied to the actual.
Proceedings Article•DOI
A real-time simulated QRS detection system constructed using wavelet filtering technique
Gulden Kokturk
06 Oct 1998
The real improvement is achieved in the wavelet filtering method and discrete wavelet analysis.
Proceedings Article•DOI
Fourier and wavelet spectral analysis of EMG signals in isometric and dynamic maximal effort exercise
José Luiz Dantas, Thiago Viana Camata, Maria Angélica de Oliveira Camargo Brunetto, Antonio Carlos de Moraes, Taufik Abrão, Leandro Ricardo Altimari 
11 Nov 2010
26 Citations
Wavelet based methods of signal analysis do not assume stationarity and may be more appropriate for joint time-frequency domain analysis.
Journal Article•DOI
A discovery of new features of gastropod local field potentials by application of wavelet tools.
Atsuko Schütt, Osvaldo A. Rosso, Alejandra Figliola 
15 Sep 2002-Journal of Neuroscience Methods
13 Citations
In respect to describing time evolution of different frequency band components the present wavelet tools can much more sensitively do so, as compared with the FAC measures.
Open access•Journal Article•DOI
What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology
Bettina Schaefli, Douglas Maraun, M. Holschneider 
01 Dec 2007-Advances in Water Resources
125 Citations
Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations.
Journal Article•DOI
An efficient wavelet-based automated R-peaks detection method using Hilbert transform
Manas Rakshit, Susmita Das 
01 Jan 2017-Biocybernetics and Biomedical Engineering
55 Citations
In this work, a wavelet transform based automated R -peaks detection method has been proposed.
Journal Article•DOI
A wavelet magnitude analysis theorem
J.C. Anderson
01 Dec 1993-IEEE Transactions on Signal Processing
The theorem presented here is one example of how GSTFT research can be beneficially applied to wavelet analysis.
Journal Article•DOI
Using wavelet transforms to analyze nonlinear ship rolling and heave-roll coupling
Yin Yu, Yin Yu, R. Ajit Shenoi, Hangbin Zhu, Lijuan Xia 
01 May 2006-Ocean Engineering
21 Citations
The investigation in this paper not only highlights the feasibility of using wavelet transforms in the analysis of nonlinear dynamic characteristics of ship rolling in waves, but also shows how it could enhance the analysis abilities.
Open access•DOI
Rate-distortion optimized geometrical image processing
R. Shukla
01 Jan 2004
13 Citations
This allows to achieve the correct exponentially decaying R-D behavior, D(R) 2-cR, thus improving over classical wavelet schemes.
Book Chapter•DOI
Multiresolution traffic prediction: combine RLS algorithm with wavelet transform
Yanqiang Luan
31 Jan 2005
Wavelet has many advantages when used in traffic analysis.
Proceedings Article•DOI
Improving myoelectric signal classification using wavelet packets and principal components analysis
Kevin Englehart, B. Hudgins, P.A. Parker, M. Stevenson 
13 Oct 1999
33 Citations
This work demonstrates how this may be achieved, using a wavelet packet based feature set in conjunction with principal components analysis.
Open access•Proceedings Article•DOI
An experimental study of induction motor current signature analysis techniques for incipient broken rotor bar detection
Norman Mariun, Mohammad Rezazadeh Mehrjou, Mohammad Hamiruce Marhaban, Norhisam Misron 
11 May 2011
In other words, wavelet analysis is superior for this purpose.
Journal Article•DOI
Some problems on the global wavelet spectrum
Shu Wu, Qinyu Liu 
01 Oct 2005-Journal of Ocean University of China
Hence it is recommended that when making period analysis with the global wavelet spectrum one needs to do further tests to confirm their results.
Book Chapter•DOI
Wavelets and Framelets Within the Framework of Nonhomogeneous WaveletSystems
Bin Han
01 Jan 2012
13 Citations
We shall see that nonhomogeneous wavelet systems naturally link many aspects of wavelet analysis together.
Book Chapter•DOI
Two-Dimensional Wavelets and their Relatives: Applications of the 2-D CWT. II: physical applications
Jean-Pierre Antoine, Romain Murenzi, Pierre Vandergheynst, Syed Twareque Ali 
01 Sep 2004
This suggests wavelet analysis.
Journal Article•DOI
Chebyshev wavelet approximation of functions having first derivative of H $$\ddot{\text {o}}$$ o ¨ lder’s class
Shyam Lal, Neha Patel 
15 Mar 2021-The São Paulo Journal of Mathematical Sciences
This is a significant achievement in wavelet analysis.
Proceedings Article•DOI
Choice of mother wavelets in CWT spectral decomposition
Satinder Chopra, Kurt J. Marfurt 
17 Dec 2015-Seg Technical Program Expanded Abstracts
29 Citations
While we do not suggest that this conclusion be generalized, we do recommend that this exercise be carried out on a test volume to select the best mother wavelet to be used in the spectral decomposition.

Related Questions

How the wavelet is used to filter cardiac signals?5 answersWavelet transforms are utilized in filtering cardiac signals to enhance diagnostic accuracy and reduce noise interference. In the context of electrocardiogram (ECG) denoising, various wavelet filter banks like the modified Mallat structure are compared for computational complexity, with the modified Mallat structure showing efficiency in ECG signal denoising. Additionally, wavelet filters are crucial in heart rate variability (HRV) analysis, where specific filters like Db-3 (Daubechies) with six-filter length are recommended for adaptive slow and fast variation detection in HRV signals. Furthermore, a study on cardiointervalography discusses the use of wavelet filters to isolate heart sounds from background noise, emphasizing the importance of filtering conditions and signal requirements. These findings collectively highlight the significant role of wavelet filters in enhancing the analysis and interpretation of cardiac signals.
Which types of wavelet are the best?4 answersThe best types of wavelet depend on the specific application. In the context of business cycle analysis in Iran, the study found that biorthogonal wavelets, particularly bior2.2, bior3.1, bior2.6, bior5.5, bior1.1, bior1.5, and bior1.3, provided the highest quality of decomposition and smoothing. For cognitive EEG classification, the Boir 2.4 wavelet type yielded the best true positive rate. In the analysis of image decomposition, Haar and Meyer wavelets demonstrated the best quality of restored image, while Daubechies wavelets, symplets, and coiflets had higher compression index. In the context of dynamic systems engineering, wavelets can be classified into orthogonal, biorthogonal, and pseudo types, with applications in vibrations analysis and systems and control analysis. For speech enhancement, the DWT Coif wavelet with soft thresholding was found to be the best for reducing noise and enhancing speech and audio signal quality.
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