Hi Jeff,

and thanks for your reply.

Well, using the symmetric haar h = [1/16 1/4 3/8 1/4 1/16] I do not have
lag effects and coefficents are in phase perfectly but I get border effects
that's unuseful to be trained with neural nets.

The same unuseful training is because of lag effects using the
1/2 1/2.

I wonder how do they do to get a perfect overlap of the coefficents as in
figure 2 with a redundant haar a trous!

The trick is just to get a wavelets that is both lag-free and without
border effect, but I have been unable to code.

Regards, Albert

2005/6/3, Jeff Winter
<j...@aeroflex.com>:

Hi Albert,

If you ignore the lag, does the result look ok?

Non-symmetric filters introduce phase shifts. The effect of a phase shift

is to displace events along the time axis; that is, if a maximum in the

original series occurs at time t0, the phase shifted maximum occurs at time

t0 + delta, where delta may be positive or negative.

So while the non-symmetric filter is important to detect edge boundaries in

this application, I think the delay is unavoidable. However, from the look

of this paper a lot of the results show the effects of de-noising the

signal? The (1/2, 1/2) filter coefficients are a simple averaging filter

that fit in with the de-noising hypothesis.

Regards,

Jeff

===================

Jeff Winter

Snr DSP Engineer

Aeroflex

www.aeroflex.com