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Shannon wavelet

In functional analysis, the Shannon wavelet (or sinc wavelets) is a decomposition that is defined by signal analysis by ideal bandpass filters. Shannon wavelet may be either of real or complex type.

Shannon wavelet is not well-localized(noncompact) in the time domain,but its Fourier transform is band-limited(compact support). Hence Shnnon wavelet has poor time localization but has good frequency localization. These characteristics are in stark contrast to those of the Haar wavelet. The Haar and sinc systems are Fourier duals of each other.

Definition

Sinc funcition is the starting point for the defintion of the shannon wavelet.

Scaling function

First, we define the scaling function to be the sinc function.

 

And define the dilated and translated intances to be

 

where the parameter   means the dilation and the translation for the wavelet respectively.

Then we can derive the Fourier transform of the scaling function:

  where the (normalised) gate function is defined by

  Also for the dilated and translated instances of scaling function:  

Mother wavelet

Use   and multiresolution approximation we can derive the Fourier transform of the Mother wavelet:

 

And the dilated and translated instances:

 

Then the shannon mother wavelet function and the family of dilated and translated instances can be obtained by the inverse Fourier transform:

 

 

Property of mother wavelet and scaling function

  • Mother wavelets are orthonormal, namely,

 

  • The translated instances of scaling function at level   are orthogonal

 

  • The translated instances of scaling function at level   are orthogonal to the mother wavelets

 

  • Shannon wavelets has an infinite number of vanishing moments.

Reconstruction of a Function by Shannon Wavelets

Suppose   such that   and for any dilation and the translation parameter  ,

 ,  

Then

  is uniformly convergent, where  

Real Shannon wavelet

 
Real Shannon wavelet

The Fourier transform of the Shannon mother wavelet is given by:

 

where the (normalised) gate function is defined by

 

The analytical expression of the real Shannon wavelet can be found by taking the inverse Fourier transform:

 

or alternatively as

 

where

 

is the usual sinc function that appears in Shannon sampling theorem.

This wavelet belongs to the  -class of differentiability, but it decreases slowly at infinity and has no bounded support, since band-limited signals cannot be time-limited.

The scaling function for the Shannon MRA (or Sinc-MRA) is given by the sample function:

 

Complex Shannon wavelet

In the case of complex continuous wavelet, the Shannon wavelet is defined by

 ,

References

  • S.G. Mallat, A Wavelet Tour of Signal Processing, Academic Press, 1999, ISBN 0-12-466606-X
  • C.S. Burrus, R.A. Gopinath, H. Guo, Introduction to Wavelets and Wavelet Transforms: A Primer, Prentice-Hall, 1988, ISBN 0-13-489600-9.

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This article provides insufficient context for those unfamiliar with the subject Please help improve the article by providing more context for the reader June 2017 Learn how and when to remove this template message In functional analysis the Shannon wavelet or sinc wavelets is a decomposition that is defined by signal analysis by ideal bandpass filters Shannon wavelet may be either of real or complex type Shannon wavelet is not well localized noncompact in the time domain but its Fourier transform is band limited compact support Hence Shnnon wavelet has poor time localization but has good frequency localization These characteristics are in stark contrast to those of the Haar wavelet The Haar and sinc systems are Fourier duals of each other Contents 1 Definition 1 1 Scaling function 1 2 Mother wavelet 1 3 Property of mother wavelet and scaling function 2 Reconstruction of a Function by Shannon Wavelets 3 Real Shannon wavelet 4 Complex Shannon wavelet 5 ReferencesDefinition EditSinc funcition is the starting point for the defintion of the shannon wavelet Scaling function Edit First we define the scaling function to be the sinc function ϕ Sha t sin p t p t sinc t displaystyle phi text Sha t frac sin pi t pi t operatorname sinc t And define the dilated and translated intances to beϕ k n t 2 n 2 ϕ Sha 2 n t k displaystyle phi k n t 2 n 2 phi text Sha 2 n t k where the parameter n k displaystyle n k means the dilation and the translation for the wavelet respectively Then we can derive the Fourier transform of the scaling function F Sha w 1 2 p P w 2 p 1 2 p if w p 0 if otherwise displaystyle Phi text Sha omega frac 1 2 pi Pi frac omega 2 pi begin cases frac 1 2 pi amp mbox if omega leq pi 0 amp mbox if mbox otherwise end cases where the normalised gate function is defined byP x 1 if x 1 2 0 if otherwise displaystyle Pi x begin cases 1 amp mbox if x leq 1 2 0 amp mbox if mbox otherwise end cases Also for the dilated and translated instances of scaling function F k n w 2 n 2 2 p e i w k 1 2 n P w 2 n 1 p displaystyle Phi k n omega frac 2 n 2 2 pi e i omega k 1 2 n Pi frac omega 2 n 1 pi Mother wavelet Edit Use F Sha displaystyle Phi text Sha and multiresolution approximation we can derive the Fourier transform of the Mother wavelet PS Sha w 1 2 p e i w P w p 3 2 P w p 3 2 displaystyle Psi text Sha omega frac 1 2 pi e i omega bigg Pi frac omega pi frac 3 2 Pi frac omega pi frac 3 2 bigg And the dilated and translated instances PS k n w 2 n 2 2 p e i w k 1 2 n P w 2 n p 3 2 P w 2 n p 3 2 displaystyle Psi k n omega frac 2 n 2 2 pi e i omega k 1 2 n bigg Pi frac omega 2 n pi frac 3 2 Pi frac omega 2 n pi frac 3 2 bigg Then the shannon mother wavelet function and the family of dilated and translated instances can be obtained by the inverse Fourier transform ps Sha t sin p t 1 2 sin 2 p t 1 2 p t 1 2 sinc t 1 2 2 sinc 2 t 1 2 displaystyle psi text Sha t frac sin pi t 1 2 sin 2 pi t 1 2 pi t 1 2 operatorname sinc bigg t frac 1 2 bigg 2 operatorname sinc bigg 2 t frac 1 2 bigg ps k n t 2 n 2 ps Sha 2 n t k displaystyle psi k n t 2 n 2 psi text Sha 2 n t k Property of mother wavelet and scaling function Edit Mother wavelets are orthonormal namely lt ps k n t ps h m t gt d n m d h k 1 if h k and n m 0 otherwise displaystyle lt psi k n t psi h m t gt delta nm delta hk begin cases 1 amp text if h k text and n m 0 amp text otherwise end cases The translated instances of scaling function at level n 0 displaystyle n 0 are orthogonal lt ϕ k 0 t ϕ h 0 t gt d k h displaystyle lt phi k 0 t phi h 0 t gt delta kh The translated instances of scaling function at level n 0 displaystyle n 0 are orthogonal to the mother wavelets lt ϕ k 0 t ps h m t gt 0 displaystyle lt phi k 0 t psi h m t gt 0 Shannon wavelets has an infinite number of vanishing moments Reconstruction of a Function by Shannon Wavelets EditSuppose f x L 2 R displaystyle f x in L 2 mathbb R such that supp FT f p p displaystyle operatorname supp operatorname FT f subset pi pi and for any dilation and the translation parameter n k displaystyle n k f t ϕ k 0 t d t lt displaystyle Bigg int infty infty f t phi k 0 t dt Bigg lt infty f t ps k n t d t lt displaystyle Bigg int infty infty f t psi k n t dt Bigg lt infty Thenf t k a k ϕ k 0 t displaystyle f t sum k infty infty alpha k phi k 0 t is uniformly convergent where a k f k displaystyle alpha k f k Real Shannon wavelet Edit Real Shannon wavelet The Fourier transform of the Shannon mother wavelet is given by PS Sha w w 3 p 2 p w 3 p 2 p displaystyle Psi operatorname Sha w prod left frac w 3 pi 2 pi right prod left frac w 3 pi 2 pi right where the normalised gate function is defined by x 1 if x 1 2 0 if otherwise displaystyle prod x begin cases 1 amp mbox if x leq 1 2 0 amp mbox if mbox otherwise end cases The analytical expression of the real Shannon wavelet can be found by taking the inverse Fourier transform ps Sha t sinc t 2 cos 3 p t 2 displaystyle psi operatorname Sha t operatorname sinc left frac t 2 right cdot cos left frac 3 pi t 2 right or alternatively as ps Sha t 2 sinc 2 t sinc t displaystyle psi operatorname Sha t 2 cdot operatorname sinc 2t operatorname sinc t where sinc t sin p t p t displaystyle operatorname sinc t frac sin pi t pi t is the usual sinc function that appears in Shannon sampling theorem This wavelet belongs to the C displaystyle C infty class of differentiability but it decreases slowly at infinity and has no bounded support since band limited signals cannot be time limited The scaling function for the Shannon MRA or Sinc MRA is given by the sample function ϕ S h a t sin p t p t sinc t displaystyle phi Sha t frac sin pi t pi t operatorname sinc t Complex Shannon wavelet EditIn the case of complex continuous wavelet the Shannon wavelet is defined by ps C S h a t sinc t e 2 p i t displaystyle psi CSha t operatorname sinc t cdot e 2 pi it References EditS G Mallat A Wavelet Tour of Signal Processing Academic Press 1999 ISBN 0 12 466606 X C S Burrus R A Gopinath H Guo Introduction to Wavelets and Wavelet Transforms A Primer Prentice Hall 1988 ISBN 0 13 489600 9 Retrieved from https en wikipedia org w index php title Shannon wavelet amp oldid 1131763539, wikipedia, wiki, book, books, library,

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