Let’s assume that a function g∈L1 satisfies the following condition.
∫Rg(y)dy∫−∞0g(y)dy∫0∞g(y)dyα+β=1=α=β=1
Furthermore, let’s say f is piecewise continuous on R. And either f is bounded, or g outside any interval [−a,a] is g=0. That is, the convolution f∗g(x) is well-defined for all x∈R. Now, let’s assume for ϵ>0, we have gϵ(y)=ϵ1g(ϵy). Then, the below equation holds.
ϵ→0limf∗gϵ(x)=αf(x+)+βf(x−),x∈R
Here, f(x+) and f(x−) are respectively the upper and lower limits of f at x. Especially if f is continuous at x, the following equation holds.
ϵ→0limf∗gϵ(x)=f(x)
Moreover, if f is continuous on some closed interval, then the mentioned convergence is uniform.
The name ‘Convolution Convergence Theorem’ is tentatively assigned due to the absence of a specific name for the theorem. It serves as a useful auxiliary theorem in Fourier analysis and distribution theory.
Proof
The equation we need to demonstrate is as follows.
ϵ→0lim∣f∗gϵ(x)−αf(x+)−βf(x−)∣=0
Arranging the inside of the absolute value gives the following.
The process of dealing with the remaining integration interval can be divided into two cases.
Case 1. If f is bounded
The second term of (eq3) can be arranged as below due to the boundedness of f. Let’s say it is ∣f∣≤M. Then,
$$
\begin{align*}
\left| \int_{c}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \right| & \le 2M \left|\int_{c}^{\infty} g_{\epsilon}(y)dy \right|
\\ & \le 2M\int_{c/\epsilon}^{\infty}\left| g(y) \right|dy \end{align*}
$$
Therefore,
ϵ→0lim∫c∞[f(x−y)−f(x−)]gϵ(y)dy=0
Case 2. When ∣x∣>a for g(x)=0
Then, whenever ∣x∣>ϵa, we have gϵ(x)=0. Then for sufficiently small ϵ,
∣x∣>c⟹gϵ(x)=0
This holds. Therefore,
ϵ→0lim∫c∞[f(x−y)−f(x−)]gϵ(y)dy=0
Thus, from (eq3), (eq4), (eq5), and (eq6), we get the following result.
ϵ→0lim∫0∞[f(x−y)−f(x−)]gϵ(y)dy=0
Applying the same method to the first term of (eq1) gives us the next.