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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.

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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
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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
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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
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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
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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
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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
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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
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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
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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
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, 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
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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
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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
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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
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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
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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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