Fixed i, j notation in proximal decoding explanation

latex/thesis/chapters/decoding_techniques.tex

@@ -743,10 +743,10 @@ the so-called \textit{code-constraint polynomial} is introduced as:%
 %
 \begin{align*}
     h\left( \boldsymbol{x} \right) =
-        \underbrace{\sum_{j=1}^{n} \left( x_j^2-1 \right) ^2}_{\text{Bipolar constraint}}
-        + \underbrace{\sum_{i=1}^{m} \left[
-            \left( \prod_{j\in \mathcal{A}
-        \left( i \right) } x_j \right) -1 \right] ^2}_{\text{Parity constraint}}%
+        \underbrace{\sum_{i=1}^{n} \left( x_i^2-1 \right) ^2}_{\text{Bipolar constraint}}
+        + \underbrace{\sum_{j=1}^{m} \left[
+            \left( \prod_{i\in N \left( j \right) } x_i \right)
+        -1 \right] ^2}_{\text{Parity constraint}}%
 .\end{align*}%
 %
 The intention of this function is to provide a way to penalize vectors far

latex/thesis/chapters/theoretical_background.tex

@@ -83,7 +83,7 @@ Lastly, the optimization methods utilized are described.
 \begin{itemize}
     \item Introduction
     \item Binary linear codes
-    \item \Ac{LDPC} codes (especially $i$, $j$, parity check matrix $\boldsymbol{H}$, etc.)
+    \item \Ac{LDPC} codes (especially $i$, $j$, parity check matrix $\boldsymbol{H}$, $N\left( j  \right) $ \& $N\left( i \right) $, etc.)
 \end{itemize}