Example for the difference between SWT and DWT

Hi,there.

I am looking for the understandable example to show the difference between DWT and SWT.

In Wavelet toolbox user's guide 3-66, it is written that "the DWT is not a time-invariant transform. This means that, even with periodic signal extension, the DWT of a translated version of a signal X is not, in general, the translated version of the DWT of X."

What does it mean?

Is there good example to show the difference?

[Good mind]

DWT=The wavelet decomposition can be described as iterative signal decomposition, using filter banks of low-pass and highpass filters (organized in a tree) with downsampling of their outputs.in each level the length of coeffs is reduced by half ex: original signal (2000) then length of coeffs from first level is 1000 an so on.

SWT=the outputs of decomposition filters in all decomposition levels are not downsampled. We can avoid interpolation errors that might occur during the reconstruction part.the length is the same in each level.

[Macy S]

Thank you for answering my question. So it seems to us that it is more useful to select SWT if I can, isn' t it?

[SHOBA MOHAN]

While using SWT, you can check memory constraints imposed by it.