[Signal and System] Filters & Bode Plot

Filters

category

低通(low-pass filter, LPF)
高通(high-pass filter, HPF)
带通(band-pass filter, BPF)
带止(band-stop filter, BSF)

We focus on low-pass filter, similar concepts and results hold for high-pass and band-pass filter.

Ideal low-pass filter: zero phase

image-20200512143142941image-20200512143158113image-20200512143220013

$$\begin{aligned}
h(t) &=\frac{1}{2 \pi} \int_{-\infty}{\infty} \mathrm{H}(j \omega) e{j \omega t} d \omega \
&=\frac{1}{2 \pi} \int_{-\omega_{c}}{\omega_{c}} 1 \cdot e{j \omega t} d \omega \
&=\left.\frac{1}{2 \pi} \cdot \frac{1}{j t} e^{j \omega t}\right|{-\omega{c}} ^{\omega_{c}} \
&=\frac{1}{2 \pi} \cdot \frac{1}{j t} \cdot 2 j \sin \left(\omega_{c} t\right) \
&=\frac{\sin \omega_{c} t}{\pi t}=\frac{\omega_{c}}{\pi} \operatorname{sinc}\left(\omega_{c} t\right) \
h(n) &=\frac{\sin \omega_{c} n}{\pi n}=\frac{\omega_{c}}{\pi} \operatorname{sinc}\left(\omega_{c} n\right)
\end{aligned}$$image-20200512144244246

\(s(t)=\int_{-\infty}^{t} h(\tau) d \tau\) image-20200512144147178

\(s(n)=\sum_{m=-\infty}^{n} h(m)\)image-20200512144216232

Ideal low-pass filter: linear phase

image-20200512144434500image-20200512144336101

rotate for \(-\alpha \omega\)

image-20200512144533776image-20200512144346387

Nonideal low-pass filter: frequencydomain

image-20200512144642077

  • Pass band: $0-\omega_{p}$, stop band: \(\omega>\omega_{s}\) transition: \(\omega_{s}-\omega_{p}\)
  • Pass-band ripple: \(\delta_{1}\), stop-band ripple: \(\delta_{2}\)Linear (nearly) linear phase over the passband is desirable.

Nonideal low-pass filter: timedomain

image-20200512144711418

  • Rise time: \(t_{r}\) overshoot: \(\Delta\)
  • Ringing frequency: \(\omega_{r}\) settling time: \(t_{s}\)

e.g. Nonideal low-pass filter

image-20200512144920810

  • Fifth-order Butterworth filter and a fifth-order elliptic filter
  • Same cutoff frequency
  • Same passband and stopband rippleThere's trade-off between time-domain characteristic \(t_{s}\) and fregurency domain characteristic \(\omega_{s}-\omega_{p}\)

Ideal vs. non-ideal filter

Gain.
  1. The ideal filter is fixed at a gain of 1 in the passband, which means that the input signal of the passband is "completely" passed, while the gain of the band is fixed at 0, which means that the input signal of the band is "completely" filtered out.
  2. The gain of a non-ideal filter is a function of frequency and not fixed.
Cut-off frequency.
  1. The ideal filter passband can be switched instantaneously between the stopband and the passband.
  2. The non-ideal filter cannot switch instantaneously between the passband and the stopband, its attenuation (gain) varies continuously with frequency, so there is a transition band, and the gain of the stopband cannot reach 0.

Bode Plot

The bode plot is for first and second-order CT system

First-order CT system

image-20200512145206265

$$\begin{aligned}
\text { Differential equation: } & C \frac{d y(t)}{d t}=\frac{x(t)-y(t)}{R} \
& \tau\left(\frac{d y(t)}{d t}\right)+y(t)=x(t), \tau=R C
\end{aligned}$$

$$\begin{aligned}
\text { Frequency response: } &\tau j \omega Y(j \omega)+Y(j \omega)=X(j \omega)\
&H(j \omega)=\frac{Y(j \omega)}{X(j \omega)}=\frac{1}{\underbrace{(j \omega \tau)+1}}_{\text {First order }}
\end{aligned}$$

Basic deduction

image-20200512145422064

image-20200512145432055

\(\tau:\) time constant
\(t=\tau, h(t)=1 /(\tau e)\)
\(s(t)=1-1 / e\) image-20200512145458290
\(\tau \downarrow, h(t)\) decays more sharply
\(s(t)\) rises more sharply

image-20200512145648470

The reason why for the image-20200512150206475 is they be approximated by the domain by the \([\frac1{10\tau},\frac{10}\tau]\) to \(-\frac4\pi[log_{10}(\omega\tau)+1]\)

Second-order CT system: differential equation

physical meaning

image-20200512145848225 image-20200512145903362

Frequency response \(\frac{d^{2} y(t)}{d t}+2 \zeta \omega_{n} \frac{d y(t)}{d t}+\omega_{n}^{2} y(t)=\omega_{n}^{2} x(t)\)

\[
\begin{array}{l}j \omega)^{2} Y(j \omega)+2 \zeta \omega_{n}(j \omega) Y(j \omega)+\omega_{n}^{2} Y(j \omega)=\omega_{n}^{2} X(j \omega) \\ H(j \omega)=\frac{\omega_{n}^{2}}{(j \omega)^{2}+2 \zeta \omega_{n}(j \omega)+\omega_{n}^{2}}\notag\end{array}
\]

image-20200512150651597image-20200512150705689

when \(\zeta>1\) the power is real, we can't apply Euler equation, just output the graph.

image-20200512150747787

some param difference in Bode

image-20200512151000940

image-20200512151016575

image-20200512151026188

image-20200512151040188

image-20200512151051914

image-20200512151101900

image-20200512151111391

implementation

image-20200512151154068

Reference

  1. Lecture Notes on Signals and Systems by Sascha Spors.[email protected]
  2. signal_system_dsp Alan V. Oppenheim