Derivation of the Optimal Matched Filter - Convolution vs. Correlation
Convolution commutes
$$
y[n]=\sum_k h[n-k]x[k]=\sum_k h[k] x[n-k]
$$
for $n=0$
$$
y[n=0]=\sum_k h[-k] x[k]
$$
If $H(e^{-\jmath \omega})$ is the Fourier Transform of $h[n]$, $H(e^{\jmath \omega})$  is the Fourier Transform of $h[-k]$, 

The maximization for the matched filter is at the point $n=0$.  

In communications $n=0$ corresponds to synchronization.

In a RADAR/SONAR problem the maximum output of the matched filter is the estimate of where $n=0$