# ShannonWavelet

represents the Shannon wavelet evaluated on the equally spaced interval {-10,10}.

ShannonWavelet[lim]

represents the Shannon wavelet evaluated on the equally spaced interval {-lim,lim}.

# Details • ShannonWavelet defines a family of orthonormal wavelets.
• ShannonWavelet[lim] is defined for any positive real lim.
• The scaling function ( ) and wavelet function ( ) have infinite support. The functions are symmetric.
• The scaling function ( ) is given by .
• The wavelet function ( ) is given by .
• ShannonWavelet can be used with such functions as DiscreteWaveletTransform and WaveletPhi, etc.

# Examples

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## Basic Examples(3)

Scaling function:

Wavelet function:

Filter coefficients:

## Scope(7)

### Basic Uses(2)

Compute primal lowpass filter coefficients:

Primal highpass filter coefficients:

### Wavelet Transforms(4)

Compute a DiscreteWaveletTransform:

View the tree of wavelet coefficients:

Get the dimensions of wavelet coefficients:

Plot the wavelet coefficients:

ShannonWavelet can be used to perform DiscreteWaveletPacketTransform:

View the tree of wavelet coefficients:

Get the dimensions of wavelet coefficients:

Plot the wavelet coefficients:

ShannonWavelet can be used to perform StationaryWaveletTransform:

View the tree of wavelet coefficients:

Get the dimensions of wavelet coefficients:

Plot the wavelet coefficients:

ShannonWavelet can be used to perform 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:

## Properties & Relations(8)

Lowpass filter coefficients approximately sum to unity; :

Highpass filter coefficients approximately sum to zero; :

Scaling function integrates to unity; :

Wavelet function integrates to zero; : 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:

With wider interval {-lim,lim}, the frequency response function approaches ideal frequency response:

Frequency response for is given by :

The filter is a highpass filter:

With wider interval {-lim,lim}, the frequency response function approaches ideal frequency response:

## Possible Issues(1)

Due to noncompact support, ShannonWavelet poorly approximates the data:

Use wider interval {-lim,lim} to improve wavelet approximation:

## Neat Examples(2)

Plot translates and dilations of scaling function:

Plot translates and dilations of wavelet function: