Questions tagged [discrete-wavelet-transform]

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Estimate Power spectral density using Discrete wavelet transform form pycwt

I want to estimate the Power spectral density using Discrete wavelet transform and a Morlet Wavelet. Bellow you can find the function I am using. Any comments or suggestions on wether or not the ...
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Practical applications of wavelets

I know wavelets were all the rage a few years ago, but I missed that boat and am wondering if it is worth putting significant effort into learning about them. My impression is that they were a little ...
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How to calculate marginal Discrete Wavelet Transform (in python)?

I need to calculate mDWT for N channels. I found a package pywavelets, that has a neat wavedec() function which I assume is similar to a Matlab one that allows me ...
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Discrete wavelet transform - DWT (beginner)

I recently stumbled upon this article: A wavelet-based multivariate multi scale approach for forecasting (PDF) In the paper they use DWT and I am having trouble understanding how to construct them. ...
2 votes
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Estimation of scaling exponent in the wavelet leaders multi-fractal formalism

I am trying to extract multi-fractal features from time-series data by estimating the singularity spectrum using the wavelet leaders multi-fractal formalism (WLMF) method. Specifically, I want to be ...
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Adjust Wavelet output to CNN

I want to extract features from the signal using DWT and then feed the results into CNN, after calling the 'dwt' library function I got a runtime error. ...
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The downsampling step with discrete wavelet transform

For one stage discrete wavelet transform (DWT), if we have a signal with 1000 samples occupying the frequency range from zero to 500 Hz, the output of the low-pass filter is a signal with frequency ...
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1 vote
1 answer
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Discrete wavelet decomposition over detail coefficients

per my understanding, if we take a 3-level discrete wavelet decomposition (DWT) over a 1-D signal with sampling rate $F_s$, we will get a series of detail and approximation coefficients, ex: [cA3, cD3,...
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Difference between Discrete Wavelet Transform and convolution

Sorry in advance if my question is too dumb. I'm going through the book of Mallat, and from what I understand, the approximation/wavelet coefficients $a_j[n] = <f, \phi_{j,n}>$ and $d_j[n] = <...
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Function reconstruction after a DWT

I'm new to this field, my apologies if my question sounds too naive. From what I understood, a function can be decomposed using the scaling function at a given scale $\{\phi_{J, k}\}_{k \in \mathbb{Z}}...
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Discrete Wavelet Transform: x-axis differences between python and MATLAB

This might be simimlar to the question: Why is there an amplitude difference in Matlab and Python?. But with the difference that I am focusing on the x-axis. To do a 5th-level decomposition, the used ...
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1D Interpolating subdivision for wavelet lifting schemes

I am looking into wavelet lifting methods first introduced by Swelden, and explained in this paper: Build your own wavelets at home. In this paper (in chapter 2 specifically), they discuss ...
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1 answer
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Polyphase Filter Implementation for oversampled (undecimated) wavelet lifting scheme?

I am learning about lifting schemes, and for my project, it seems as though it would be beneficial to use an undecimated wavelet transform (UWT). I have found a paper by Lee, Lee, and Yoo (New lifting ...
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Calculate and plot CDF 5/3 wavelet phi and psi functions

For a FOSS project I've to work with the CDF 5/3 wavelet. And while I understand the implementation by lifting scheme and my code works well, I want to understand the math theory behind wavelets in ...
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How to do appcoef and detcoef using pyWavelets?

I am new to signal processing and currently doing a school project in wavelet transform using Python. I want to extract all details and approximations (Example: cA2, cA1, cD2, cD1), pywt could return ...
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Multilevel DWT wavedec - How to get each coefficient (approximations and details) in the same length as the original signal?

I am doing a school project referring to the research paper https://www.tandfonline.com/doi/abs/10.1080/0952813X.2013.813976?journalCode=teta20 The overall concept of the research is as the following ...
1 vote
1 answer
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Should i use window with hop_size in Wavelet Transform or Discrete Wavelet Transform?

I have a signal (audio - voice) with 1 second of duration with sample rate of 50000 Hz. It is big signal and I wish extract some features and apply pattern recognition or classification. My question ...
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1 answer
238 views

How could I do a Discrete Fourier Transform in Python if my data is non uniform?

I have been trying to find a way to transform my time series data in an equivalent manner to the discrete Fourier transform. What I wish to find is something like: ...
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What exactly is meant by "translation invariant dictionaries/wavelets"?

I'm trying to wrap my head around the notion of translation invariance in terms of dictionaries/wavelets. For example in Lecture Notes, Page 41 its written that one starts with a family of atoms/...
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4 votes
3 answers
937 views

Continuous Wavelet Transform vs Discrete Wavelet Transform

The discrete wavelet transform is applied in many areas, such as signal compression, since it is easy to compute. I notice that, However, the continuous wavelet transform (CWT) is also applied to ...
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Extract signals with certain frequenceis from a data sample using python

I did not major in signal processing, and I do not know a lot about some possibly very basic facts, so although SE has some questions related to this, I still have some confusion. I am given a data ...
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What does the intensity values on wavelet transform mean? Amplitude or power?

So when applying wavelet transform, we get a 2d plot. Each point in that 2d plot has a color, showing intensity of something. But I cannot understand if it is an amplitude or power?
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How to find the Wavelet measurement matrix in compressed sensing?

Assume that an image vector x = Ψs. s is a sparse vector in which the image vector x of length N x 1 is sparse in the wavelet Ψ basis. I have issue in finding the measurement matrix A= φ Ψ where φ is ...
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1 answer
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Waveform pattern detection in time series

I have some IMU data which I am using to detect activity patterns - walking, running etc. In order to differentiate one activity from another I need to do pattern matching in time series. Different ...
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Wavelet, scaling, detail, and smooth/approximation coefficients

I was reading through the documentation for the R wavelets package and doing a little experimentation and noticed that the modwt ...
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567 views

PyWavelets SWT versus MODWT

I'm just learning about wavelets and the PyWavelets package. I saw a reference to MODWT, which led me to the SO post here and then to this Python package: https://github.com/pistonly/modwtpy What ...
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Pros/Cons to using Spectral and Diffusive Graph Wavelets

As I understand, there are two major methods of constructing wavelets on graphs. Spectral wavelets, from David K Hammond et. al, and diffusive wavelets from Coifman and Maggioni. I can't quite parse ...
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What does the sample entropy of a digital signal mean?

What sample entropy signifies about a signal and how it used to analyse a signal?
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1 answer
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Why discrete wavelet transforms use sampling rate 2 and need signal length to be a power of 2?

I know Fourier transforms but new to wavelet transforms. I can understand Haar transform needs signal length a power of 2, since the filters have 2 taps and down-sampling and up-sampling in the ...
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Does the Fast Wavelet Transform produce the same coefficient as the Discrete Wavelet Transform?

Does the Fast Wavelet Transform(FWT) produce the same coefficients as the Discrete Wavelet Transform(DWT) if configured for the same depths? Or is the the FWT just an approximation of the DWT?
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