RGann
- 12
- 1
A seemingly good way to understand the overshoot and decay (ringing) of a square wave on a scope is that it is the result of bandwidth limiting. In that case, the Fourier series of a square wave
\Pi(t) = \frac{1}{2 \pi} \sum_{n=-\infty}^\infty \frac{\sin(n \omega/2)}{n \omega/2} \exp(i n \omega t)
shows the well-known overshoot when n is only taken to a small number, such as 30, terms.
It's obtained by Fourier transforming the rect function \Pi(t) to get \mathrm{sinc}(\omega), then transforming back to the time domain, except you form a Riemann sum instead of an integral and take finite terms.
But this calculation doesn't reproduce what you really see on a scope, because it appears to be non-causal. That is, before the machine that drives the signal starts to apply voltage (at t=-5 in the plot), this curve is already ringing. There's a few references to the causality being related to the Kramer's-Kronig relations, especially in the "Understanding the Kramers-Kronig Relation Using A Pictorial Proof" white paper availble online (here). In that they suggest forming a causal function, where it is zero for all t < 0, which we could do by translating the rectangle function so that its rise is at t=0. Then form even and odd functions out of the signal. When you do this, the odd function is the same as the even function times \mathrm{sgn}. However, this seems to be of little help, particularly because finding the Fourier transform of the odd part
h_o = \mathrm{sgn}(t) h_e = (1/2) \mathrm{sgn}(t) \Pi(t)
involves a convolution of \mathrm{sinc} and 1/i \omega, which is quite difficult (Wolfram integrator gives an answer that is not pure imaginary, which shouldn't be true).
What am I missing here? Is there a way to present the real signal you see on a scope trace as an instance of the Gibbs phenomenon? If so, is this on the right track? Does anyone know of a treatment of this problem?
Thanks!
\Pi(t) = \frac{1}{2 \pi} \sum_{n=-\infty}^\infty \frac{\sin(n \omega/2)}{n \omega/2} \exp(i n \omega t)
shows the well-known overshoot when n is only taken to a small number, such as 30, terms.
It's obtained by Fourier transforming the rect function \Pi(t) to get \mathrm{sinc}(\omega), then transforming back to the time domain, except you form a Riemann sum instead of an integral and take finite terms.
But this calculation doesn't reproduce what you really see on a scope, because it appears to be non-causal. That is, before the machine that drives the signal starts to apply voltage (at t=-5 in the plot), this curve is already ringing. There's a few references to the causality being related to the Kramer's-Kronig relations, especially in the "Understanding the Kramers-Kronig Relation Using A Pictorial Proof" white paper availble online (here). In that they suggest forming a causal function, where it is zero for all t < 0, which we could do by translating the rectangle function so that its rise is at t=0. Then form even and odd functions out of the signal. When you do this, the odd function is the same as the even function times \mathrm{sgn}. However, this seems to be of little help, particularly because finding the Fourier transform of the odd part
h_o = \mathrm{sgn}(t) h_e = (1/2) \mathrm{sgn}(t) \Pi(t)
involves a convolution of \mathrm{sinc} and 1/i \omega, which is quite difficult (Wolfram integrator gives an answer that is not pure imaginary, which shouldn't be true).
What am I missing here? Is there a way to present the real signal you see on a scope trace as an instance of the Gibbs phenomenon? If so, is this on the right track? Does anyone know of a treatment of this problem?
Thanks!