FIR filters - page 3
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on the X axis bars t h e time axis
coefficients values on y-axis
this graph shows the response of the filter to a unit pulse, you can compare how a gap appeared after a perfect flat
The unit pulse is the derivative of the step, i.e. delta function?
You're a hundred and one measuring entities, I haven't looked at the software yet and I don't know what its output is or what its input is.
and you don't need to know the software.
in other words - how do you cascade the filters based on these limitations?
Is the unit impulse a derivative of the step, i.e. a delta function?
Yeah, it's kind of like a flat gap and flat again at a new level.
sab1uk, is it possible to formalize dependence between spectral estimate (say, found a period of a wave with maximum amplitude) and fatl/satl-type filter parameters? Thanks.
The well-known fatls and satls are low-pass filters with compromised parameters, i.e. the amplitude-frequency response (AFC) is not steep
If you want a steeper amplitude-frequency response you will need to use more frequent filter adaptations.
I tried reading the "Filtering bourgeois bazaars" thread on viac, the guys there discussed/wrote this software. It is clear, that one can get FIR filter by looking at spectrum with eyes. But if spectrum is "floating", how can one follow it in automatic mode?
It'd be weird if it didn't float.
I wanted first of all to show people that there is a good alternative to the machetes
Agree, all other things being equal, running after the floating spectrum is better armed with a normal filter instead of a machete
why wipers don't think of the running away spectrum i don't know
After all, the use of wizards does not relieve from the problem of non-stationarity
It'd be weird if it didn't float.
I wanted first of all to show people that there is a good alternative to the machetes
Agree, all other things being equal, running after the floating spectrum is better armed with a normal filter instead of a machete
why wipers don't care about the running away spectrum I don't know
because use of flappers does not relieve from a problem of non-stationarity
The digital method generator is made with a mistake. The author apparently counts the coefficients correctly, but only uses half of those coefficients.
The signal should be multiplied by the whole impulse response. As a result, the resulting filter has nothing to do with the specified parameters.
Firstly, it is 2 times shorter. Therefore, it is sort of "faster". Secondly, the frequency response does not provide the specified suppression.
The code for MQL4 from the "Digital Method Generator" isn't what the author wanted.
Any indicator based on the "Numerical Method Generator" will not filter exactly as the author intended.
The filtering is much worse than expected, but the delay is less because the filter is shorter.
What kind of filtering is needed? I have no idea. But I prefer to understand what I'm doing.
As an example of a FIR filter you can try an LPF based indicator with a Kaiser window.
This approximation allows you to get a lot of suppression. Although in my
my opinion, increasing the delay negates the advantages of filtering.
But it is difficult to cheat nature, though it would be very desirable. The greater the suppression,
the greater the length of the filter and therefore the lag.