Convolution

A mathematical operation that combines 2 functions to produce a third expressing how the shape of one is modified by the other. Denoted by ∗*.

(f∗g)(t)=∫−∞∞f(τ) g(t−τ) dτ(f * g)(t) = \int_{-\infty}^{\infty} f(\tau) \, g(t - \tau) \, \text{d}\tau

Slides one function over another, multiplying and integrating at each shift.

Properties

  • Commutative
    f∗g=g∗ff * g = g * f
  • Associative
    f∗(g∗h)=(f∗g)∗hf * (g * h) = (f * g) * h
  • Distributive
    f∗(g+h)=(f∗g)+(f∗h)f * (g + h) = (f * g) + (f * h)
  • Identity
    f∗δ=ff * \delta = f, where δ\delta is the Dirac delta function

Convolution Theorem

Laplace

The Laplace transform of a convolution is the product of the individual Laplace transforms.

Suppose L{f}=F\mathcal{L}\{f\} = F and L{g}=G\mathcal{L}\{g\} = G:

L{f∗g}=F(s) G(s)\mathcal{L}\{f * g\} = F(s) \, G(s)

Useful for solving ODEs: multiply in the ss-domain, then apply the inverse Laplace transform.

Fourier

F{f∗g}=F(ω)⋅G(ω)\mathcal{F}\{f * g\} = F(\omega) \cdot G(\omega)

Convolution in the time domain equals pointwise multiplication in the frequency domain. Used extensively in signal processing and filter design.

Written by September 29, 2026 1 min read
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