convolution vs correlation?
Convolution:

$$ y(t) = h(t) \circledast x(t) = \int\limits_{-\infty}^{\infty} h(u) \, x(t-u) \ \mathrm{d}u $$

Cross Correlation:

$$ R_{xy}(t) = \int\limits_{-\infty}^{\infty} y(u) \, x(t+u) \ \mathrm{d}u $$

The difference between the two is effectively the sign on $u$ in $x(t-u)$ in the integral.  That correlation is like convolution but with one of the signals flipped left to right is essentially the basis of the Matched Filter.