From: W. Trevor King <wking@tremily.us>
Date: Mon, 27 May 2013 11:22:49 +0000 (-0400)
Subject: calibcant/theory.tex: Use en-dashes (--) for Wiener-Khinchin
X-Git-Tag: v1.0~120
X-Git-Url: http://git.tremily.us/?a=commitdiff_plain;h=26c84ab358466d727aeac60bb368caaf01322048;p=thesis.git

calibcant/theory.tex: Use en-dashes (--) for Wiener-Khinchin

This matches the Wikipedia URL ('%E2%80%93' codes for U+2013 EN DASH).
---

diff --git a/src/calibcant/main.bib b/src/calibcant/main.bib
index e38fda5..d27d06f 100644
--- a/src/calibcant/main.bib
+++ b/src/calibcant/main.bib
@@ -50,7 +50,7 @@
 }
 
 @Misc{wikipedia-wiener-khinchin,
-  title = "{W}iener-{K}hinchin theorem",
+  title = "{W}iener--{K}hinchin theorem",
   publisher = "Wikipedia",
   url = "http://en.wikipedia.org/wiki/Wiener\%E2\%80\%93Khinchin_theorem",
   day = "TODO",
diff --git a/src/calibcant/theory.tex b/src/calibcant/theory.tex
index 86ac487..ed602cf 100644
--- a/src/calibcant/theory.tex
+++ b/src/calibcant/theory.tex
@@ -86,12 +86,13 @@ where $t_T$ is the total time over which data has been aquired.
 \nomenclature{$\abs{z}$}{Absolute value (or magnitude) of $z$.  For
   complex $z$, $\abs{z}\equiv\sqrt{z\conj{z}}$.}
 
-We also use the Wiener-Khinchin theorem,
+We also use the Wiener--Khinchin theorem,
 which relates the two sided power spectral density $S_{xx}(\omega)$
 to the autocorrelation function $r_{xx}(t)$ via
 \begin{align}
   S_{xx}(\omega) &= \Four{ r_{xx}(t) } \;,
-       &\text{(Wiener-Khinchin)\citep{wiener-khinchin}} \label{eq:wiener_khinchin}
+       &\text{(Wiener--Khinchin)\citep{wiener-khinchin}}
+    \label{eq:wiener_khinchin}
 \end{align}
 \index{Wiener-Khinchin theorem}
 where $r_{xx}(t)$ is defined in terms of the expectation value
@@ -137,7 +138,7 @@ We compute the \PSD\ by plugging \cref{eq:ODHO-xmag} into
 \end{equation}
 \index{PSD@\PSD}
 
-Because thermal noise is white (not autocorrelated + Wiener-Khinchin
+Because thermal noise is white (not autocorrelated + Wiener--Khinchin
 Theorem), we can write the one sided thermal power spectral density
 per unit time as
 \begin{equation}