represents a Coiflet wavelet of order 2.
CoifletWavelet [n]
represents a Coiflet wavelet of order n.
CoifletWavelet
represents a Coiflet wavelet of order 2.
CoifletWavelet [n]
represents a Coiflet wavelet of order n.
Details
- CoifletWavelet defines a family of orthogonal wavelets.
- CoifletWavelet [n] is defined for positive integers n between 1 and 5.
- The scaling function () and wavelet function () have compact support of length . The scaling function has vanishing moments and wavelet function has vanishing moments.
- CoifletWavelet can be used with such functions as DiscreteWaveletTransform , WaveletPhi , WaveletPsi , etc.
Examples
open all close allBasic Examples (3)
Scaling function:
Wavelet function:
Filter coefficients:
Scope (12)
Basic Uses (7)
Compute primal lowpass filter coefficients:
Primal highpass filter coefficients:
Lifting filter coefficients:
Generate a function to compute a lifting wavelet transform:
Coiflet scaling function of order 1:
Coiflet scaling function of order 4:
Plot scaling function at different refinement scales:
Coiflet wavelet function of order 1:
Coiflet wavelet of order 4:
Plot wavelet function at different refinement scales:
Wavelet Transforms (4)
Compute a DiscreteWaveletTransform :
View the tree of wavelet coefficients:
Get the dimensions of wavelet coefficients:
Plot the wavelet coefficients:
Compute a DiscreteWaveletPacketTransform :
View the tree of wavelet coefficients:
Get the dimensions of wavelet coefficients:
Plot the wavelet coefficients:
Compute a StationaryWaveletTransform :
View the tree of wavelet coefficients:
Get the dimensions of wavelet coefficients:
Plot the wavelet coefficients:
Compute a StationaryWaveletPacketTransform :
View the tree of wavelet coefficients:
Get the dimensions of wavelet coefficients:
Plot the wavelet coefficients:
Higher Dimensions (1)
Multivariate scaling and wavelet functions are products of univariate ones:
Applications (3)
Approximate a function using Haar wavelet coefficients:
Perform a LiftingWaveletTransform :
Approximate original data by keeping n largest coefficients and thresholding everything else:
Compare the different approximations:
Compute the multiresolution representation of a signal containing an impulse:
Compare the cumulative energy in a signal and its wavelet coefficients:
Compute the ordered cumulative energy in the signal:
The energy in the signal is captured by relatively few wavelet coefficients:
Properties & Relations (11)
Lowpass filter coefficients sum to unity; :
Highpass filter coefficients sum to zero; :
Scaling function integrates to unity; :
In particular, :
Wavelet function integrates to zero; :
Wavelet function is orthogonal to the scaling function at the same scale; :
The lowpass and highpass filter coefficients are orthogonal; :
satisfies the recursion equation :
Plot the components and the sum of the recursion:
satisfies the recursion equation :
Plot the components and the sum of the recursion:
Frequency response for is given by :
The filter is a lowpass filter:
The higher the order n, the flatter the response function at the ends:
Fourier transform of is given by :
Frequency response for is given by :
The filter is a highpass filter:
The higher the order n, the flatter the response function at the ends:
Fourier transform of is given by :
Possible Issues (1)
CoifletWavelet is restricted to n less than 5:
CoifletWavelet is not defined when n is not a positive machine integer:
Neat Examples (2)
Plot translates and dilations of scaling function:
Plot translates and dilations of wavelet function:
Tech Notes
Related Guides
History
Text
Wolfram Research (2010), CoifletWavelet, Wolfram Language function, https://reference.wolfram.com/language/ref/CoifletWavelet.html.
CMS
Wolfram Language. 2010. "CoifletWavelet." Wolfram Language & System Documentation Center. Wolfram Research. https://reference.wolfram.com/language/ref/CoifletWavelet.html.
APA
Wolfram Language. (2010). CoifletWavelet. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/CoifletWavelet.html
BibTeX
@misc{reference.wolfram_2025_coifletwavelet, author="Wolfram Research", title="{CoifletWavelet}", year="2010", howpublished="\url{https://reference.wolfram.com/language/ref/CoifletWavelet.html}", note=[Accessed: 09-January-2026]}
BibLaTeX
@online{reference.wolfram_2025_coifletwavelet, organization={Wolfram Research}, title={CoifletWavelet}, year={2010}, url={https://reference.wolfram.com/language/ref/CoifletWavelet.html}, note=[Accessed: 09-January-2026]}