Generator

A 3.0 kHz input sampled at 10 kHz arrives as itself

computed by solving, not by drawing. The dots are the samples. The input at 3.00 kHz is below half the 10 kHz rate, so the only sinusoid through these dots below half the rate is the one that was sampled. That is the whole of what the sampling theorem promises, and it stops promising it at 5.00 kHz.
A 3.0 kHz input sampled at 10 kHz arrives as itselfcomputed by solving, not by drawing. The dots are the samples. The input at 3.00 kHz is below half the 10 kHz rate, so the only sinusoid through these dots below half the rate is the one that was sampled. That is the whole of what the sampling theorem promises, and it stops promising it at 5.00 kHz.the input, 3.00 kHzsample rate10.0 kHzhalf of it5.00 kHzinput3.00 kHzreported as3.00 kHzsamples differ by0.0e+0solved, then checked — one sequence, two sourceshalf the sample rate: 5.00 kHz

Drawn above at its default parameters, which is almost never how an essay calls it. A placement states the numbers that essay is arguing about, so the figure a reader meets is about that argument rather than about the generator — 98% of the placements on this site pass one, and the phase that raised that number from 12% found eight captions describing a figure the page was not showing.

At those defaults the edge it states is half the sample rate: 5.00 kHz — the right-hand slot of the caption strip, which on this site is never used for anything else, and which is read back out of the drawing above rather than out of the code that wrote it. It belongs to Where a signal becomes a number, which is to say a change to it is a change to lib/figures/digital.js. It takes a slider on input frequency (kHz) with 8 settings, and every one of them has passed the same assertions as the frame above — a figure whose circuit stops doing what its caption says at any setting stops the build.

Called by 6 essays

which is the blast radius of changing it

The frequency a sample rate invents

Every other boundary on this site is a model getting gradually worse. This one has no gradient at all: below half the sample rate a set of samples has one sinusoid through it, above half the sample rate it has another, and the two sets of numbers are identical to three parts in ten thousand billion. Nothing is attenuated, nothing is distorted, and there is no measurement of the samples that could say which signal was there.

Where a signal becomes a number

An exact answer to a different question

The reconstruction that turns samples back into a signal is normally introduced as the thing that recovers what was there. Measured on both sides of half the sample rate it does something more interesting than failing: above the boundary it returns the alias to 1.6 parts in a thousand, which is the same accuracy it returns the input with below the boundary, and it is wrong about the input by twice the amplitude. Its error is not a degradation. It is exactness about something else.

Where a signal becomes a number

What the filter in front costs

The filter that keeps a converter honest is normally chosen for its skirt. Measured against one requirement — eighty decibels down by the frequency that folds back into a 20 kHz band — the choice is not a decibel or two of skirt but a factor in the clock: Bessel demands 3.53 times Nyquist, Butterworth 2.08, Chebyshev 1.53. And one design is refused outright, because an elliptic stopband is a floor rather than a slope and no sample rate reaches past a floor.

Where a signal becomes a number

A resistor made of a clock

A capacitor shuttled between two nodes at a megahertz behaves as a megohm, and a tenth of a picofarad shuttled at ten kilohertz behaves as a gigohm — which is how a filter with a one-hertz corner fits on a chip. What the equivalence costs is three conditions, and they bind on three different quantities: a capacitor ratio under 0.0201, a signal below half the clock, and a clock below the frequency at which the charge stops arriving.

Filters, measured not tabulated

A floor, or a line

Two clocks with identical two-picosecond jitter sample the same sinusoid, and the total error power is the same to a tenth of a decibel — the closed form the rung below computed, right for both. One of them puts that error across two thousand bins at −120 dB each; the other puts it into two lines at −91.5. The gap is the processing gain, it grows with the record length because a density falls and a line does not, and nothing in a specification quoted in picoseconds root-mean-square distinguishes the two cases.

Where a signal becomes a number

The nulls are where nothing is

A zero-order hold multiplies the whole repeated spectrum by one sinc, so it attenuates every image at the image's own frequency and its nulls land exactly on the multiples of the clock. Nothing is ever at a null: the two first-order images straddle it, and the closer the signal comes to half the clock the closer they come to each other. The hold gives 25.6 dB of image rejection to a tone at a twentieth of the clock, 1.74 dB at 0.45 of it, and nothing at all at half — which is the frequency the band most needs it at.

Where a signal becomes a number

Every generator