--- title: "Convolution theorem" firstLetter: "C" publishDate: 2021-02-22 categories: - Mathematics date: 2021-02-22T21:35:23+01:00 draft: false markup: pandoc --- # Convolution theorem The **convolution theorem** states that a convolution in the direct domain is equal to a product in the frequency domain. This is especially useful for computation, replacing an $\mathcal{O}(n^2)$ convolution with an $\mathcal{O}(n \log(n))$ transform and product. ## Fourier transform The convolution theorem is usually expressed as follows, where $\hat{\mathcal{F}}$ is the [Fourier transform](/know/concept/fourier-transform/), and $A$ and $B$ are constants from its definition: $$\begin{aligned} \boxed{ \begin{aligned} A \cdot (f * g)(x) &= \hat{\mathcal{F}}^{-1}\{\tilde{f}(k) \: \tilde{g}(k)\} \\ B \cdot (\tilde{f} * \tilde{g})(k) &= \hat{\mathcal{F}}\{f(x) \: g(x)\} \end{aligned} } \end{aligned}$$ To prove this, we expand the right-hand side of the theorem and rearrange the integrals: $$\begin{aligned} \hat{\mathcal{F}}^{-1}\{\tilde{f}(k) \: \tilde{g}(k)\} &= B \int_{-\infty}^\infty \tilde{f}(k) \Big( A \int_{-\infty}^\infty g(x') \exp(i s k x') \dd{x'} \Big) \exp(-i s k x) \dd{k} \\ &= A \int_{-\infty}^\infty g(x') \Big( B \int_{-\infty}^\infty \tilde{f}(k) \exp(- i s k (x - x')) \dd{k} \Big) \dd{x'} \\ &= A \int_{-\infty}^\infty g(x') f(x - x') \dd{x'} = A \cdot (f * g)(x) \end{aligned}$$ Then we do the same thing again, this time starting from a product in the $x$-domain: $$\begin{aligned} \hat{\mathcal{F}}\{f(x) \: g(x)\} &= A \int_{-\infty}^\infty f(x) \Big( B \int_{-\infty}^\infty \tilde{g}(k') \exp(- i s x k') \dd{k'} \Big) \exp(i s k x) \dd{x} \\ &= B \int_{-\infty}^\infty \tilde{g}(k') \Big( A \int_{-\infty}^\infty f(x) \exp(i s x (k - k')) \dd{x} \Big) \dd{k'} \\ &= B \int_{-\infty}^\infty \tilde{g}(k') \tilde{f}(k - k') \dd{k'} = B \cdot (\tilde{f} * \tilde{g})(k) \end{aligned}$$ ## Laplace transform For functions $f(t)$ and $g(t)$ which are only defined for $t \ge 0$, the convolution theorem can also be stated using the Laplace transform: $$\begin{aligned} \boxed{(f * g)(t) = \hat{\mathcal{L}}^{-1}\{\tilde{f}(s) \: \tilde{g}(s)\}} \end{aligned}$$ Because the inverse Laplace transform $\hat{\mathcal{L}}^{-1}$ is unpleasant, the theorem is often stated using the forward transform instead: $$\begin{aligned} \boxed{\hat{\mathcal{L}}\{(f * g)(t)\} = \tilde{f}(s) \: \tilde{g}(s)} \end{aligned}$$ We prove this by expanding the left-hand side. Note that the lower integration limit is 0 instead of $-\infty$, because we set both $f(t)$ and $g(t)$ to zero for $t < 0$: $$\begin{aligned} \hat{\mathcal{L}}\{(f * g)(t)\} &= \int_0^\infty \Big( \int_0^\infty g(t') f(t - t') \dd{t'} \Big) \exp(- s t) \dd{t} \\ &= \int_0^\infty \Big( \int_0^\infty f(t - t') \exp(- s t) \dd{t} \Big) g(t') \dd{t'} \end{aligned}$$ Then we define a new integration variable $\tau = t - t'$, yielding: $$\begin{aligned} \hat{\mathcal{L}}\{(f * g)(t)\} &= \int_0^\infty \Big( \int_0^\infty f(\tau) \exp(- s (\tau + t')) \dd{\tau} \Big) g(t') \dd{t'} \\ &= \int_0^\infty \Big( \int_0^\infty f(\tau) \exp(- s \tau) \dd{\tau} \Big) g(t') \exp(- s t') \dd{t'} \\ &= \int_0^\infty \tilde{f}(s) g(t') \exp(- s t') \dd{t'} = \tilde{f}(s) \: \tilde{g}(s) \end{aligned}$$ ## References 1. O. Bang, *Applied mathematics for physicists: lecture notes*, 2019, unpublished.