I just had an idea, I was wondering if its been done and tested before.
if you take a sample, and resample it to half - then you lose half the
frequencies because they are now above nyquist (theyve lost their
compression or rarefaction.)
that will give you a low pass filter.
you shrink the sample set to lose the his- then you reenlarge it to keep
it in the same time set.
then to get a high pass filter its the original sound minus the lows,
band pass is a lowpass filter and highpass filter combined.
so you could actually make a filter library out of resamples, and its
actually not computationally expensive, and it
has instant reaction - and iir and fir filters take a few samples to
kick in (the higher order they are the more they
woomph the sound in), so this is actually better in a way!
to get so theres no distortion, youd have to implement anti aliasing.
is this a valid way to make a filter?, or is it not accurate enough to
work properly. and has it been done before?
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It’s definitely a valid way to make the filter. The question is how do
you do the resampling.
If you do the resampling the “standard” way, by averaging, you’ve just
implemented a box filter. It can be used to make high-pass, low-pass,
and bandpass filters, but comes with the standard problems of box
filters in that it’s a sinc filter in the frequency domain, and so you
can get “ringing” due to the bits of high frequencies that are let
However, you can also resample using other filters, like Gaussians or
In fact, trying to evaluate wide filters, like wide Gaussians for
instance, is much faster if you first downsample the image a bit, then
do the Gaussian, and then upsample. The results can look visually
wow, i never thought of this.
do u think doing it this way, you could get a correct partial exactly (a
is there any place on the internet where they are using this method i
could have a read?
I’m sorry, I don’t know what you mean by a “correct partial”? Are you
talking about a kind of filter?
a single sinewave.
anyway - i read on the internet and you can use am to close a chosen
frequency to 1 hz by using a sine wave oscillating at it.
all frequencies above the sine wave dont make it to 1 hz and the sine
waves below back flip at 0 hz.
so you need a low pass filter that can isolate 1 hz.
Can you give me a link? I’m sorry, I’m still not quite understanding
what you’re talking about.
It sounds like you’re talking about a perfect low-pass filter, with an
infinitely sharp falloff (all frequencies above the cutoff are perfectly
attenuated, all frequencies below are perfectly undistorted)?
That would be a box filter in the frequency domain, which by the fourier
transform would be equivalent to an (infinite-extent) sinc filter in the
im sorry if im confusing…
im trying to implement something like this->
i want a filter with infinitely sharp falloff, yep.
sorry, i dont know what im talking about…