Note that if one samples a signal twice at frequencies whose ratio is not a rational number (say 1.0 and π), the first sample by itself would be unable to distinguish between DC and integer multiples of 1.0Hz, while the second could be unable to distinguish between DC and integer multiples of πHz.

2011年4月22日 · Frequency is the inverse of time for repeating events. If a single cycle of your mains is 1/50 of a second in duration (0.02 seconds), then there will be 50 cycles in a second (1 / 0.02).

2021年8月9日 · It is not possible to have a frequency of 0Hz. There is a categorical change when you go from approaching 0, to exactly 0. If something has a frequency, it’s better to think of it in terms of powers of ten, the frequency doesn’t go between 0 and infinity, it goes between 10 to the power of -infinity, and 10 to the power of +infinity.

In other words, '0Hz' means this value is applied to the entire signal, ie. it is added (as an offset) to every sample. with audio that is generally undesirable (some algorithms don't like it), so if a particular recording or ADC converter produced an unwanted DC offset you can use a …

2014年12月20日 · Transients are more difficult to categorize, but again it's a matter of timeframe. The average on the time window would give DC, and the rest AC. A Fourier transform is more strict, defining DC as 0Hz. Theoretically Fourier transforms are only for periodic signals, but one can assume any signal capture repeats itself and proceed. \$\endgroup\$

2020年6月1日 · And thinking that as a result you can choose any period since as long as it has an amplitude of zero there will always be zero oscillation? I would also disagree that the period of a constant signal is undefined (unless you consider infinite to be undefined). It is infinite which is the same as 0Hz. \$\endgroup\$ –

2020年5月11日 · so I've been attempting to do a FFT on some data and I'm seeing a peak at 0Hz, which I can't really comprehend why since I'm quite new to signal processing. I read in my file using pandas, saved them to arrays and used scipy's FFT function on the y data. But when plotting it against a frequency linspace the results seem odd to me.

A hertz is a cycle per second. Audio is compressed air, in some periodic way, so for 440hz for example, the compression change from fully compressed to fully decompressed 440 times per second.

2021年3月16日 · $\begingroup$ This looks more like the result of a kink in the input function, that is, the function is continuous, also as periodic continuation, but the derivative has a jump, most likely at the wrap-around.

2019年12月26日 · Your signal is a square wave with its base at 0V and its peak at 2.7V or so. So it has an average voltage of 1.35V. In the frequency domain, the overall average of a signal is its content at DC or 0Hz -- so that's why there's a peak at 0Hz. The FFT of a square wave that is centered on 0V has energy at every odd harmonic, starting at 1.