Re-export everything

content/zettels/decimation.md

@@ -69,7 +69,7 @@ where \\(F\\) is the ratio of single-stage low pass filter's transition region w
 F = \frac{f\_{\text{stop}} - B^\prime}{f\_{\text{stop}}}
 \end{equation}
 
-After using Eq. \ref{eq:M1opt} to determine the optimum first downsampling factor, and setting \\(M\_1\\) equal to the integer sub-multiple of \\(M\\) that is closest to \\(M\_{1,\text{opt}}\\), the second downsampling factor is:
+After using Eq. \eqref{eq:M1opt} to determine the optimum first downsampling factor, and setting \\(M\_1\\) equal to the integer sub-multiple of \\(M\\) that is closest to \\(M\_{1,\text{opt}}\\), the second downsampling factor is:
 
 \begin{equation} \label{eq:M2\_from\_M1}
 M\_2 = \frac{M}{M\_1}
@@ -89,9 +89,9 @@ N = \frac{\text{Atten}}{22 (f\_{\text{stop}} - f\_{\text{pass}})} = \frac{60}{22
 which is way too large for practical implementation.
 
 To reduce the number of necessary filter taps, we can partition the decimation problem into two stages.
-With \\(M = 100\\), \\(F = (2200-1800)/2200\\), Eq. \ref{eq:M1opt} yields \\(M\_{1,\text{opt}} = 26.4\\).
+With \\(M = 100\\), \\(F = (2200-1800)/2200\\), Eq. \eqref{eq:M1opt} yields \\(M\_{1,\text{opt}} = 26.4\\).
 The integer sub-multiple of 100 closest to \\(26.4\\) is \\(25\\), so we set \\(M\_1 = 25\\).
-Next, from Eq. \ref{eq:M2\_from\_M1}, \\(M\_2 = 4\\) is found.
+Next, from Eq. \eqref{eq:M2\_from\_M1}, \\(M\_2 = 4\\) is found.
 
 The first low pass filter has a pass-band cutoff frequency of \\(1.8\\,kHz\\) and its stop-band is \\(400/25 - 1.8 = 14.2\\,kHz\\) ([Figure 4](#figure--fig:decimation-two-stage-example) (d)).
 The second low pass filter has a pass-band cutoff frequency of \\(1.8\\,kHz\\) and its stop-band is \\(4-1.8 = 2.2\\,kHz\\).
@@ -116,16 +116,18 @@ There are two **practical issues** to consider for two-stage decimation:
 
 In order to cope with the second issue, an efficient decimation filter implementation scheme called _polyphase decomposition_ can be used.
 
-<summary>The advantages of two stage decimation, over single-stage decimation are:
+<div class="sum">
 
-<ul class="org-ul">
-<li>an overall reduction in computation workload</li>
-<li>reduced signal and filter coefficient data storage</li>
-<li>simpler filter designs</li>
-<li>a decrease in the ill effects of finite binary-work-length filter coefficients</li>
-</ul>
+The advantages of two stage decimation, over single-stage decimation are:
 
-These advantages become more pronounced as the overall desired decimation factor \(M\) becomes larger.</summary>
+-   an overall reduction in computation workload
+-   reduced signal and filter coefficient data storage
+-   simpler filter designs
+-   a decrease in the ill effects of finite binary-work-length filter coefficients
+
+These advantages become more pronounced as the overall desired decimation factor \\(M\\) becomes larger.
+
+</div>
 
 
 ### References: {#references}