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Conventional telephone service wiring sends signals in both directions simultaneously using a 'hybrid'. Wikipedia - Telephone Hybrid


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Those words which are used to describe statistical distributions - how they differ from the Gaussian bell curve - are not common when one wants to describe with words how a pulse looks in an oscilloscope. That's because elecric circuits can have even much more complex forms of voltages vs. time, there's no "normal pulse form". If you have a noise ...


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That depends very highly on the specific conditions or application you look at. I don't know of any general rule of how to interpret these statistical parameters in regard to electrical measurements, you really need context to do this. I can only give you one example from my area of work: When you measure the sEMG (very small voltages on the surface of your ...


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Technically, the Laplace transform already implies a causal system by its definition: $$F(s)=\int_0^\infty f(t)e^{-st}dt$$ As you can see, the integral starts from 0, so this implies that \$f(t < 0) = 0\$. In other words, a non-causal system would react before it received the Dirac pulse or \$f(t < 0) \neq 0\$. A regular Laplace transform would not ...


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I'm being very handwavy, but... Interpreting the skewness or kurtosis of a distribution isn't actually so straight-forward, even in the setting of plain old probability theory. What you need to realize is that these "higher-order moments" are "just" (i.e., modulo some details, scaling, etc) the coefficients of the Maclaurin expansion of ...


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One way you can achieve "placeable zeros" is by using a dynamic feedback. As given in the question, this is what you achieved with constant feedback on three loops: $$G(z)=\frac{1}{z-1}$$ $$\text{NTF(z)}=\frac{1}{\left(1+\frac{\alpha}{z-1}\right)\left(1+\frac{\beta}{z-1}\right)\left(1+\frac{\gamma}{z-1}\right)}$$ $$\text{NTF(z)}=\frac{(z-1)^3}{(z-1+...


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I mean to write this as a comment but it ended up too long. Since you don't give numeric values to the coefficients then you can only solve this symbolically. As you correctly say in your comment (and as I hinted at earlier) that particular transfer function will give 4 roots: two positive and two negative. Since you need the Hurwitz polynomial, you'll need ...


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Yes it is realizable, convert the transfer function to state space: Source: https://math.stackexchange.com/questions/2463007/if-a-state-space-realization-a-b-c-d-is-minimal-will-its-inverse-also-be-m There are many forms you could then realize (cascade, canonincal, and parallel, I chose canonical), it will look like this, but with an additional integrator (...


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The calculations make little sense, as they have mixed up various different terms together. NTSC basically means analog composite video signal with of 4.2 MHz video bandwidth, where using System M standard 525 lines is sent every 29.97 Hz with NTSC color encoding. If that is digitized into digital composite video, it is usually sampled at 4x the color ...


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Since it's a completely hypothetical situation, it's difficult to guess how they came up with those numbers. In fact, the NTSC signal devotes less bandwidth to representing color, and the entire baseband signal can be adequately represented by sampling it at 13.5 MHz with 8-bit samples, for a raw data rate of just 108 Mbps. And that could be reduced ...


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They use 704 for the horizontal x 480 vertical, which is typical for MPEG-2. That works out to 162Mbit/s. That's their mistake - they're putting the MPEG cart before the horse in computing the raw pixel rate for CCIR656-type format. They should have either computed it based on 720 or explained why they used 704. Speaking of which... why 704? Part of the ...


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How can I evaluate the SNR in such a case? The signal power is \$V_{SIG}^2/R\$ The noise power is \$V_{NOISE}^2/R\$ So, when you take the ratio (aka signal to noise ratio or SNR) the resistance \$R\$ cancels and you are left with: - $$SNR = \dfrac{V_{SIG}^2}{V_{NOISE}^2}$$


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