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1

The formulas for cutoff frequencies of a bandpass filter are different for different filter designs and can be calculated from the transfer function $H(ω)$. For a "basic" series RLC filter $$ H(ω) = {\frac {ωRC} {\sqrt{(1-ω^2LC)^2 + (ωRC)^2}} } $$ and this filter can be made narrowband if implemented with a high quality factor (see later in this ...


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The FFT is equivalent to a bank of FIR band pass filters, in python you can compute the fft using numpy.fft.fft, and the central normalized (with respect to sampling rate) frequency of each filter is obtained with numpy.fft.fftfreq For real signals you can use numpy.fft.rfft and numpy.fft.rfftfreq If you want implementation guidance in stack overflow, give ...


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In audio applications, this would be a low-cut filter. The term is often used synonymous with high pass, though that would not accurately describe general zero-mean filters. A unit-mean filter meanwhile is indeed a lowpass filter.


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In complement to Marcus, I have read the term "zero-sum": "zero-sum window", "zero-sum filter", "zero-sum kernel", the latter being more frequent. It is similar to "unit-sum windows", ie windows whose amplitudes sum to one. "Zero-average" can be found in image processing: Further note that applying ...


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"Zero-Mean" is the word that's commonly used to describe signals and signals with a zero average. "This is a zero-mean filter." If you really mean a filter that is specifically meant to cancel the DC component, a "DC blocker" is a name for that.


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From one of your comments it appears that you've actually already answered the question. Here are a few remarks and questions that should help you gain some more understanding: If you have a transfer function $H(z)$ (and if you assume that the corresponding system is stable), then the frequency response is obtained by choosing $z=e^{j\omega}$. For $H(z)=z^{-...


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A pure delay is also an all-pass filter because $$ |H(e^{j\omega})| = 1 $$ But it's an FIR version of an APF filter.


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Multiplication in the frequency domain is the equivalent of convolution (digital filtering) in the time domain - one of the fundamental properties of the Fourier transform. Using an FFT in practice to filter requires stitching together overlapping chunks and a large delay if in real-time. However in the frequency domain you can immplement brick-wall filters ...


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The reason the bandpass filter eliminated the problem is because it removed the DC component. This can also be done by simply subtracting the average before taking the DFT. However there is much more to understand in this question that should be of interest to the OP, and after reading and understanding the detail given below, this first statement should ...


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