Syndrome decoding ($s=H{y}^T=H{e}^T$)

For a linear code with parity-check matrix $H$, write the received word as $y=c+e$, where $c$ is a codeword and $e$ an error pattern. Its syndrome depends only on the error because $H{c}^T=0$. A syndrome decoder chooses a representative error $\hat{e}$ with that syndrome and returns $y-\hat{e}$. Choosing a minimum-Hamming weight representative gives minimum-distance decoding; within the guaranteed correction radius it recovers the unique transmitted codeword. Several representatives may tie outside that radius.