Wavelet Analysis

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5 What is the difference between empirical mode decomposition (EMD) and wavelet transform?
By Pinki Sharma · Indian Institute of Information Technology Allahabad

Guilherme Welter · Laboratório Nacional de Computação Científica

Regarding online signal processing, Flandrin's group proposed an online EMD algorithm: http://perso.ens-lyon.fr/patrick.flandrin/NSIP03.pdf

Regarding online signal processing, Flandrin's group proposed an online EMD algorithm: http://perso.ens-lyon.fr/patrick.flandrin/NSIP03.pdf

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4 What is the potential of Bio-signal (EEG and ECGl) as biometrics?
By Pinki Sharma · Indian Institute of Information Technology Allahabad

Ulrich Hofmann · Universität Freiburg

I am not convinced that ECG or EEG signals can be used for a reliable high-end biometric systems. The signals are i) just to easily influenced by non-... [more]

I am not convinced that ECG or EEG signals can be used for a reliable high-end biometric systems. The signals are i) just to easily influenced by non-obvious parameters, ii) to difficult to get reliable/reproducible access to and iii) to cumbersome to acquire in huge numbers for a data base.... ad i) just think even with a clinically attached multi-lead ECG on the variations in heartbeat during a day... ad ii) Influences are e.g. mood, health status, electrode contact, positioning.... All these parameters are influencing the measurements. Completely different from a finger print! ad iii) a data base must contain a huge number of recognizable/labeled data sets. I somehow would not very happily spend hours with providing EEG signals under many different conditions.... Please enlighten me, if you have a way to overcome this reliability issues.

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Question:
Open Denoising with Tree-Structure Wavelets
Hi everyone, I try to repeat the result of Section 5.3 of the paper "Proximal Methods for Hierarchical Sparse Coding" by R. Jenatton .et.al by using ... [more]

Hi everyone, I try to repeat the result of Section 5.3 of the paper "Proximal Methods for Hierarchical Sparse Coding" by R. Jenatton .et.al by using mexProximalTree function their SPAMS toolbox http://spams-devel.gforge.inria.fr/index.html. If anyone has any ideas about "Wavelet-based denoising by hierarchical norm", please drop me a hint. Regards Cat Le

By Anh Cat Le Ngo · University of Nottingham, Malaysia Campus

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5 How to convert .eeg file to .mat file in matlab?
By Chirag Thummar · Hochschule Anhalt

Pedro Galindo · Universidad de Cádiz

You can use the following function within matlab to load the *.eeg file: http://sccn.ucsd.edu/~arno/programs/loadeeg.m To use it, just write... [more]

You can use the following function within matlab to load the *.eeg file: http://sccn.ucsd.edu/~arno/programs/loadeeg.m To use it, just write: signal = loadeeg( 'myfile.eeg' ); To save to a matlab file, just write: save myfile.mat signal

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2 I need help in wavelets based analysis of time series data
By Shivappa Sobarad · Basaveshwar Engineering College, Bagalkot

Guilherme Welter · Laboratório Nacional de Computação Científica

Dear Shivappa Sobarad, this question is very broad. Could you give more details about your question?

Dear Shivappa Sobarad, this question is very broad. Could you give more details about your question?

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3 For discret wavelet analysis , how we decorrelate data, a stationarize the signal

Guilherme Welter · Laboratório Nacional de Computação Científica

If you want to distroy all the correlations in a signal then you have to randomize (shuffle) the signal. This will preserve the original PDF of the si... [more]

If you want to distroy all the correlations in a signal then you have to randomize (shuffle) the signal. This will preserve the original PDF of the signal but its spectrum will be flat. However, if you want to decrease the correlation between two different signals while keeping some properties, then you should try surrogate or bootstrap methods, such as the (Iterative) Amplitude Adjusted Fourier Transform. There also wavelet based variants. Regarding stationarization, that depends on the type of non-stationarity your data have. You always have to consider the properties in your data you want to preserve and those you want to destroy. For example, if the non-stationarity is regarding the presence of trends in the data, you could try the Empirical Mode Decomposition for signal detrending .

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3 Are there databases available for Photplethysmogram (PPG) using mobile phone camera?
By Arpan Pal · Tata Consultancy Services Limited

James Taylor · Cardiac Science Corporation

For SaO2, normally one LED is red, with wavelength of 660 nm, and the other is infrared, 940 nm. To measure bilirubin a blue LED, 460 nm or to measur... [more]

For SaO2, normally one LED is red, with wavelength of 660 nm, and the other is infrared, 940 nm. To measure bilirubin a blue LED, 460 nm or to measure carboxyhemoglobin, a 500 or 550 nm LED might be added. Looking at: http://www.andor.com/learning-academy/ccd-spectral-response-(qe)-defining-the-qe-of-a-ccd The infrared measurement might be a problem - although at 50% sensitivity this still might be OK. Since there are isosbestic points at 586 nm and near 808 nm one might do with a 586 nm LED. Accurate control over wavelength is critical though. For normal range heart rates, I'd suggest you could make a pretty good measurement, at 80-120 fps, up-sampling to accurately make peak measurements. You may even have an advantage, since rather than strobing, and interleaving LEDs at each frequency, you might run the LEDs simultaneously and identify frequency by placement of the LED in the CCD frame. Frame sampling jitter between frequencies would then be non-critical. Resolution could be enhanced by estimating intensity distribution across multiple pixels.

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14 How can I relate wavelets to the theory of music?
By Maliheh Akbari Motlagh · Ferdowsi University Of Mashhad

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3 Wavelet coefficients are stationary at each scale??

Patrice Brault · French National Centre for Scientific Research

In fact your question embedds two : for the second it is yes. For the first one (in your "title"), I would answer no. For example, think of the bulb o... [more]

In fact your question embedds two : for the second it is yes. For the first one (in your "title"), I would answer no. For example, think of the bulb of Saint Basile Cathedral in Moscow. At a high resolution, for each bulb, you will find a strong coeff at the position of the summit (the center) of the bulb. But if you move left or right from the summit your maximal coefficient will be found at a lower scale. The line of maxima, when going through scales, is not vertical but bends on either sides of the center, which means that through scales the maximal coefficient is not "stationary" in position. It is the same kind of lines which is used in multifractal analysis for finding the singularity spectrum (see WTMM , wavelet transform maxima method).

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1 Local fractional wavelet transform
By Akbar Esmaeelzadeh · Qazvin Islamic Azad University

Patrice Brault · French National Centre for Scientific Research

As far as I know it was proposed by Yang and you can follow this link to get more help. summary of his book here : http://www.nonlinearscience.com/dow... [more]

As far as I know it was proposed by Yang and you can follow this link to get more help. summary of his book here : http://www.nonlinearscience.com/downloads/toc-yang.pdf Author page http://works.bepress.com/yang_xiaojun/ Matlab code may be asked to the same author.

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Answer added to:
1 Local fractional wavelet transform was proposed by Yang.
By Yang Xiao-Jun · China University of Mining & Technology Beijing Graduate School

Akbar Esmaeelzadeh · Qazvin Islamic Azad University

Hi dear Yang Is there any implementation (matlab) for this transform? Do you ever used it in signal processing filed? is there any comparison between ... [more]

Hi dear Yang Is there any implementation (matlab) for this transform? Do you ever used it in signal processing filed? is there any comparison between it's results with common wavelet (proposed by Mallat) results? tnx

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Answer added to:
7 What is the best tool for EMG classification?
By Rabya Khan · COMSATS Institute of Information Technology

Fariba Biyouki · Islamic Azad University Mashhad Branch

Hello Rabya, I sent the article to your email. I hope you will get it. Best wishes,

Hello Rabya, I sent the article to your email. I hope you will get it. Best wishes,

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2 Can any body send the code of Curvelet Transform
By Prabhakar T · Anna University, Chennai

Jose Mejia · Universidad Autónoma de Ciudad Juárez

or visit the site : http://www.curvelet.org/ under software, where is the latest version of CurveLab

or visit the site : http://www.curvelet.org/ under software, where is the latest version of CurveLab

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Answer added to:
3 GGD is used for modelling DWT wavelet coefficients of natural images (Do 2002). Can it be generalized for other types of wavelet ?
By Anh Cat Le Ngo · University of Nottingham, Malaysia Campus

Anh Cat Le Ngo · University of Nottingham, Malaysia Campus

Besides GGD, wavelet coefficients can also be effectively modeled by Gaussian Mixture Model (GSM). Using GSM with Hidden Markov Tree model, we have a ... [more]

Besides GGD, wavelet coefficients can also be effectively modeled by Gaussian Mixture Model (GSM). Using GSM with Hidden Markov Tree model, we have a tool to investigate statistical relations such as inter-band, intra-band correlation, etc. Google scholar for the term Wavelet Hidden Markov Model will lead you to several relating publications. Hope those information helps for researchers who have similar questions in mind.

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14 EMG signal processing techniques: any suggestions?
By Parthiban Kesavan · University of Auckland

Praveen Gupta · Malaviya National Institute of Technology Jaipur

Try Hilbert -Huang Transform ..........

Try Hilbert -Huang Transform ..........

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1 Multiresolution Analysis
By Mehdi Bastani · Azerbaijan Shahid Madani University

Dimitri Petritis · Université de Rennes 1

Hello, Yes, it is necessary that the spaces V_j are closed, otherwise you haven't any immediate notion of basis to decompose vectors. To be able to d... [more]

Hello, Yes, it is necessary that the spaces V_j are closed, otherwise you haven't any immediate notion of basis to decompose vectors. To be able to do that, you must be sure that converging sequences of vectors in V_j tend to vectors of V_j.

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3 Introductory notes about DWT?
By Oualid Bada · Rheinische Friedrich-Wilhelms-Universität Bonn

Yang Xiao-Jun · China University of Mining & Technology Beijing Graduate School

The theory of local fractional wavelet analysis is a new tool to process non-differential functions in fractal space

The theory of local fractional wavelet analysis is a new tool to process non-differential functions in fractal space

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4 Do you know of theoretical results on peaks or center frequency of Daubechies wavelets (locations, convergence, etc.)?
By Laurent Duval · IFP Energies nouvelles

Alexandru Isar · Polytechnic University of Timisoara

Yes, I hope.

Yes, I hope.

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2 How can wavelet analysis be used to analyse very large genomic sequences?
By Shiwani Saini · Sharda University

Shiwani Saini · Sharda University

Thanks for your help but this paper does not sort my problem

Thanks for your help but this paper does not sort my problem

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Question:
Open Wavelet Packet Modulation PSD?
Dose anybody know how to calculate Wavelet Packets PSD on reconstruction output with MatLab? I did it using IFFT's output in OFDM, but it looks worse ... [more]

Dose anybody know how to calculate Wavelet Packets PSD on reconstruction output with MatLab? I did it using IFFT's output in OFDM, but it looks worse now.

By Hadi Rafiei Azar · University of Tabriz

Following
Question:
Open Approximation coefficients
Can approximations undergo linear regression? Does it depending on the original signal?

Can approximations undergo linear regression? Does it depending on the original signal?

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4 How to Acquire exact signal after multiple decomposition using mdwt, when the signal is generated for a DNA sequence
By Ma Pa · The Maharaja Sayajirao University of Baroda

Liu Shuaiqi · Institut informacijskih znanosti

I think you should read some book of the basic filter of wavelet. what' more, you can just using the wavelet toolbox for applications.

I think you should read some book of the basic filter of wavelet. what' more, you can just using the wavelet toolbox for applications.

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11 Choosing a mother wavelet for a image.
By Theresa Cenate · Sathyabama University

Theresa Cenate · Sathyabama University

Laurent Sir, My Matlab version is not supporting the codes. I am trying to make use of ssim as you suggested

Laurent Sir, My Matlab version is not supporting the codes. I am trying to make use of ssim as you suggested

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8 Choice of level of decomposition

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The choice in signal is not a real problem, my problem is the perfect choice of the decomposition level

The choice in signal is not a real problem, my problem is the perfect choice of the decomposition level

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Answer added to:
1 How we choise the level of decomposition ,,??

Dimitris Roulias · University of Patras

i use to count kurtosis and skewness for each level. At the level that kurtosis is closer to 3 and skew close to zero means that you have reached cont... [more]

i use to count kurtosis and skewness for each level. At the level that kurtosis is closer to 3 and skew close to zero means that you have reached contextual noise and no further information may exist in your decomposed signal. And there i stop. A priori knowledge of the nature of the physics of the system may also guide you. The energy is one criterion also, but there is a possibility that useful information may be of low energy and may loose it.

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Answer added to:
13 Drawback of discrete wavelet analysis

Shahid Qamar · International Islamic University, Islamabad

but there are advantages of DWA. I want to know the draw backs of Wavelets transform and different between fourier and wavelets tranform.

but there are advantages of DWA. I want to know the draw backs of Wavelets transform and different between fourier and wavelets tranform.

Following
Question:
Open the step od decompostion in DWT
1/ at each step, the number of data is reduced by /2 , how at each scale of decomposition, the number of points still the same despite of reduction o... [more]

1/ at each step, the number of data is reduced by /2 , how at each scale of decomposition, the number of points still the same despite of reduction of coefficients by/2?? 2/ how decomposition is benefical if the number of coefficients is reduced by /2, there is a loss of informations ?? 3/ if we have calculated the high level of decompostion (j), decompose once again (j+1) means we will change the appearance of orignal signal ( theirs propreties ..) or it does not have any effects ??

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3 wavelets analysis
By Mohamed EL Hacen Ould Mohamed Dyla

Laurent Duval · IFP Energies nouvelles

You are very welcome. Good luck with your research

You are very welcome. Good luck with your research

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2 Review paper on 2D wavelet bases and frames, and related tools
By Laurent Duval · IFP Energies nouvelles

Laurent Duval · IFP Energies nouvelles

Dear Sattar Thank you for your kind message. Best regards

Dear Sattar Thank you for your kind message. Best regards

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2 the group in wavelet analysis
By Congwei Song ·

Congwei Song ·

The modular function of the topological group is \Delta(a,b)=1/|a|, with Haar measure dadb/a^2. The Duflo-Moore Operator is FAf=Ff(x)/|x|, where Ff(x)... [more]

The modular function of the topological group is \Delta(a,b)=1/|a|, with Haar measure dadb/a^2. The Duflo-Moore Operator is FAf=Ff(x)/|x|, where Ff(x)/x is in L^2.

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About Wavelet Analysis

Signal and data processing method that uses decomposition of wavelets to approximate, estimate, or compress signals with finite time and frequency domains. It represents a signal or data in terms of a fast decaying wavelet series from the original prototype wavelet, called the mother wavelet. This mathematical algorithm has been adopted widely in biomedical disciplines for data and signal processing in noise removal and audio/image compression (e.g., EEG and MRI).

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Bilal Ghazal

Lebanese University
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French National Centre for Scientific Research
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University of Science and Technology, Beijing
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Zürcher Hochschule für Angewandte Wissenschaften
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Bharat Institute of Engineering and Technology
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Universidad de Málaga
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University of Tehran

Wavelet Analysis

About Wavelet Analysis

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