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