Re: DWT anti-causality



Jerry Avins wrote:

The filter delay is built into the problem; low frequencies at high
sample rates make for long filters. Downsampling the data is simply an
efficient way to downsize the filter. Using a different filter that
enables you to avoid downsampling won't decrease your delay.

Put differently, you can either downsample the data or increase the
filter length for each pass. That increases memory use but doesn't
change the delay.


Right - I'll end up doubling the filter length for each level and end
up with the same situation. Ok, scratch that idea.

How about my initial one, that didn't work - simply using an expanding
window? For each sample you transform it and the previous samples. You
then only keep the last sample from each transform. I know it is
computationally atrocious, but still, it should eliminate the delay, at
least explicitly. It didn't work for me (i suspect) because of the
boundary problems due to padding, but I'm thinking it's possible to
work around the problem by using such window lengths that no padding is
necessary. In that situation, there will be a delay, but it will be
constant for all decomposition levels.

.



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