updates
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@@ -267,11 +267,9 @@ Hamming distance is a metric.
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### Level of error handling
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error detection
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erasure correction
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error correction
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- error detection
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- erasure correction
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- error correction
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Erasure: replacement of an entry by $*\not\in F$.
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@@ -283,11 +281,27 @@ Example: If $d_H(\mathcal{C})=d$.
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Theorem: If $d_H(\mathcal{C})=d$, then there exists $f:F^n\to \mathcal{C}\cap \{\text{"error detected"}\}$. that detects every patter of $\leq d-1$ errors correctly.
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\* track lost *\
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- That is, we can identify if the channel introduced at most $d-1$ errors.
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- No decoding is needed.
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Idea:
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Since $d_H(\mathcal{C})=d$, one needs $\geq d$ errors to cause "confusion$.
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Since $d_H(\mathcal{C})=d$, one needs $\geq d$ errors to cause "confusion".
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<details>
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<summary>Proof</summary>
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The function
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$$
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f(y)=\begin{cases}
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y\text{ if }y\in \mathcal{C}\\
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\text{"error detected"} & \text{otherwise}
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\end{cases}
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$$
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will only fails if there are $\geq d$ errors.
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</details>
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#### Erasure correction
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@@ -295,7 +309,11 @@ Theorem: If $d_H(\mathcal{C})=d$, then there exists $f:\{F^n\cup \{*\}\}\to \mat
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Idea:
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\* track lost *\
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Suppose $d=4$.
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If $4$ erasures occurred, there might be two possible codewords $c,c'\in \mathcal{C}$.
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If $\leq 3$ erasures occurred, there is only one possible codeword $c\in \mathcal{C}$.
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#### Error correction
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