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In signal processing, a filter is a device or process that transforms a signal by selectively choosing specific frequencies and leaving others with appropriate gain or as it is.

phase ones do what you claim. The point is that (although you're basically asking us to write a textbook on filter and signal theory) you'd typically understand filters as systems with poles and zeros …
answered Feb 8 '16 by Marcus Müller
The obvious answer: define a mathematical model of how the temperature affects your data, and use that model to remove the effect of temperature on your data. Sorry, but with the amount of informatio …
answered Feb 4 '16 by Marcus Müller
There's no known name for this kind of filter in the signal processing world, as far as I know – and what good would such a name be, anyway? So, I'd describe it in a signal processing context as "dis …
answered Apr 19 '19 by Marcus Müller
Aside from your discontinuity problems, which have nothing to do with your filter, but the way you apply it, there's the fact that you're specifying one system, and then building a different one: …
answered May 11 '19 by Marcus Müller
This sounds like a job for a simple high-pass filter, followed by a simple threshold, to me. 1/3 billion records isn't much data if you're used to radio signal sampling rates, so computationally, thi …
answered Nov 19 '18 by Marcus Müller
However, it seems rather inefficient to implement two separate filters. Would it not be more efficient to implement a single filter, and then subtract the output from the original signal to … )->(+) --> | ^ | | -----> ↓2 --> Delay----/ Now, your LPF is a FIR filter. Without wanting to explain all of Polyphase filters, you can, without any problem, take a …
answered Oct 27 '16 by Marcus Müller
My immediate approach to this: try something that I'd call a running-minimum filter: Look at a fixed amount of $N$ samples around the current sample. If the current sample is significantly below that …
answered Aug 27 '17 by Marcus Müller
carrier in a given bandwidth, would be a band-edgel FLL; simply put: let's have two overlapping band pass filters. If the upper one sees more power than the lower one, the signal isn't centered … estimators for different pulse shaping filters. Timing recovery You wanted to use the Polyphase Clock Sync timing estimator, which is an excellent choice – it uses a bank of slightly shifted filters
answered Aug 17 '16 by Marcus Müller
An easy way to deal with this would be to actually let the sine run through your filter for a while, and then just at the right phase save the state of the IIR. However, chances are: if the impulse r …
answered Nov 14 '19 by Marcus Müller
, same slide, explicitly: We can design filters for any other cut-off frequency by substituting $s$ by $\frac s{\omega_c}$. …
answered Nov 19 '16 by Marcus Müller
Is there a name for such a kind of filter? No. (Ok, there probably is, but it's not commonly used) The point is that your filter is not a linear system, and thus has properties that make it unsu …
answered Feb 14 '17 by Marcus Müller
If the formula becomes the same, the response becomes the same – there's no difference to be expected.
answered Aug 15 '17 by Marcus Müller
What this gain actually means? The factor between in- and output amplitudes for a signal in the passband Does it compensates for the amplitude scaling inherent to upsampling? Ex …
answered Aug 24 '16 by Marcus Müller
That depends. But typically, yes, you'll flush out your transmit signal; that basically "costs" nearly nothing, but makes sure your spectral mask stays clean. At the receiver, this part still contrib …
answered Jun 14 '19 by Marcus Müller
I ran your code and made a magnitude response plot: import numpy import scipy.signal from matplotlib import pyplot try: import seaborn except: pass #graphs won't be as pretty *shrug* fs = 2 …
answered Aug 19 '16 by Marcus Müller

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