Boundary effect in a wavelet multi resolution analysis What are the methods to minimize the effect of boundaries in a wavelet decomposition?
I use R and the package waveslim.
I have found for instance the function
?brick.wall

but

*

*I am not too use how to use it.


*I am not sure the best solution is to remove some coefficient. I have read somewhere that it exists some wavelets that are not the same everywhere and their shape change at the boudaries.
Any ideas?
 A: I think this is a good question and I don't kown much about implementations. Since wavelet is 'mutli-resolution' you have two types of solutions (which are somehow connected): 


*

*Modify your signal for example extend you signal over the actual boundary to have meaningfull coefficients.
Exemples of that are : 


*

*periodic wavelet on the interval

*Zero padding (extend the signal by zero outside ist domain

*finer prodecure are extensions of zero padding with smoothness condition at the boundary. 


*Modify the wavelet (somehow equivalent to threshold or lower wavelet coefficient that are near the boundary). More generally, there are procedures I know there have been many work  since that of A Cohen I Daubechies et P Vial   1993. For example, in (Monasse and Perrier, 1995), wavelet that forms a basis adapted to conditions such as Dirichlet or Neumann are constructed. I guess some are implemented ? If you found implementations, I am interested. 
References:
Monasse and Perrier : 1995 CRAS Ondelettes sur lintervalle pour la prise en compte de conditions aux limites
A Cohen  I Daubechies et P Vial  Wavelets on the interval and fast wavelet transforms    Appl Comp Harmonic Analysis  (1993)
