clean derivation with summary table

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Lieuwe Leene 2025-01-03 18:51:10 +01:00
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@ -149,47 +149,40 @@ characteristics for generated polynomials.
Specifically polynomials of even orders with real roots such Specifically polynomials of even orders with real roots such
that we can decompose the polynomial \\(P(x)\\) as a product of several that we can decompose the polynomial \\(P(x)\\) as a product of several
elements in the form of \\( (x+p_1)(x+p_2) \\). We can show that the elements in the form of \\( (x+p_1)(x+p_2) \\). We can show that the
fourier-transform of of this element is in the form of \\( sinc(d ω)^4 \\) fourier-transform of of this element is in the form of \\( sinc(d ω)^2 \\)
where \\( d = (p_1 - p_2)/2 \\) such that we can resolve the transform for where \\( d = (p_1 - p_2)/2 \\) such that we can derive relations for the
\\( P(x) = (x+d)(x-d) \\) polynomial \\( P(x) = d^2-x^2 \\) and scale them accordingly.
First consider a simple box function of
width \\( d/4 \\) and its corresponding fourier transform:
$$ $$
S(x) = \begin{cases} \hat{P}(x) = \int^{d/2}_{d/2} (d^2-x^2) cos(k x) dx
1 &\text{if |x| <= d/4 } \\\\ \quad = \quad
0 &\text{otherwise } \frac{8 \sin{ (d k) }}{k^3} - \frac{8 d \cos{ (d k ) }}{k^2}
\end{cases} \quad \xrightarrow{\mathfrak{F}} \quad \frac{d}{2} sinc( \frac{d\omega}{4} )
$$ $$
We can auto-convolve \\(S(x)\\) twice in order to realize a parabola with roots at We can numerically solve for some of the filter properties of interest and
+/- d. First formulate the associated triangle function \\(T(x)\\): compare to other simple windows. There is little suprise in the table below
as the roll-off and rejection is closely related to the 3dB bandwidth.
Here we see that the frequency response of P(x) is somewhere inbetween a
rectangular window and that of the raise-cosine or Hann window.
| Property | 2nd Order Poly len(2d) | Rectangle len(2d) | Hann len(2d) |
|---------------|------------------------|-----------------------|-----------------------|
| DC Value | \\(\frac{2d^3}{3}\\) | \\(2d^2\\) | \\(2d^2\\) |
| 3db Bandwidth | \\(\sim 2.498/d\\) | \\(\sim 1.895/d\\) | \\(\sim 3.168/d\\) |
| 1st Null | \\(\sim 4.5/d\\) | \\(\frac{\pi}{d}\\) | \\(\frac{2\pi}{d}\\) |
| Roll Off | 40 dB / decade | 20 dB / decade | 60 dB / decade |
For completeness we also include the analytical expression for the Hann window
frourier transform.
$$ $$
T(x) = S(x) \ast S(x) = \int_{-d/2}^{d/2} S(\tau) S(x-\tau) d\tau \quad = \begin{cases} \hat{H}(x) = \int^{d/2}_{d/2} (1+cos(\frac{2\pi x}{d})) cos(k x) dx
0 &\text{if x < -d/2 } \\\\ \quad = \quad
(x+d/2) &\text{if x < 0 } \\\\ \frac{2 \pi^2 sin(d k)}{k(d^2 k^2-\pi^2)}
(d/2-x) &\text{if x < d/2 } \\\\
0 &\text{otherwise}
\end{cases}
$$
The second auto-convolution of \\(T(x)\\) gives back the parabola \\(P(x)\\):
$$
P(x) = T(x) \ast T(x) = \int_{-d}^{d} T(\tau) T(x-\tau) d\tau = \begin{cases}
d^2/4 - x^2/4 &\text{if |x| <= d } \\\\
0 &\text{otherwise }
\end{cases}
$$ $$
$$
P(x) \quad \xrightarrow{\mathfrak{F}} \quad \frac{d^4}{16} sinc(\frac{d\omega}{4} )^4
$$
## References: ## References: