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This commit is contained in:
2025-02-11 19:43:58 -08:00
committed by Mark
parent 61a43e11ec
commit 57cd8d63a8
2 changed files with 44 additions and 6 deletions

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@ -570,8 +570,45 @@ If we know which parity bits are inconsistent, how can we find where the error i
\vfill
\problem{}<generalize-hamming>
Can you generalize this system for messages of 4, 64, or 256 bits?
Generalize this system for messages of 4, 64, or 256 bits. \par
\begin{itemize}
\item How does the resilience of this scheme change if we use a larger message size?
\item How does the efficiency of this scheme change if we send larger messages?
\end{itemize}
\vfill
\pagebreak
\definition{}
A \textit{deletion} error occurs when one bit of the message is deleted. \par
Likewise, an \textit{insertion} error consists of a random inserted bit. \par
\definition{}
A \textit{message stream} is an infinite string of binary digits.
\problem{}
Show that Hamming codes do not reliably detect bit deletions: \par
\hint{
Create a 17-bit message whose first 16 bits are a valid Hamming block, \par
and which is still valid when a bit (chosen by you; not the $17^\text{th}$) is deleted.
}
\vfill
\problem{}
Convince yourself that Hamming codes cannot correct insertions. \par
Then, create a 16-bit message that...
\begin{itemize}
\item is a valid Hamming block, and
\item incorrectly "corrects" a single bit error when it encounters an insertion error.
\end{itemize}
\vfill
As we have seen, Hamming codes effectively handle substitutions, but cannot reliably
detect (or correct) insertions and deletions. Correcting those errors is a bit more difficult:
if the number of bits we receive is variable, how can we split a stream into a series of messages? \par
\note{This is a rhetorical question, which we'll discuss another day.}
\pagebreak