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Convolution Convergence Theorem 📂Fourier Analysis

Convolution Convergence Theorem

Theorem

Let’s assume that a function gL1g \in L^{1} satisfies the following condition.

Rg(y)dy=10g(y)dy=α0g(y)dy=βα+β=1 \begin{align*} \int_{\mathbb{R}}g(y)dy &= 1 \\ \int_{-\infty}^{0}g(y)dy &= \alpha \\ \int_{0}^{\infty}g(y)dy &=\beta \\ \alpha+\beta &= 1 \end{align*}

Furthermore, let’s say ff is piecewise continuous on R\mathbb{R}. And either ff is bounded, or gg outside any interval [a,a][-a,a] is g=0g=0. That is, the convolution fg(x)f \ast g(x) is well-defined for all xRx\in \mathbb{R}. Now, let’s assume for ϵ>0\epsilon >0, we have gϵ(y)=1ϵg(yϵ)g_{\epsilon}(y)=\frac{1}{\epsilon}g(\frac{y}{\epsilon}). Then, the below equation holds.

limϵ0fgϵ(x)=αf(x+)+βf(x),xR \lim \limits_{\epsilon \to 0}f \ast g_{\epsilon}(x)=\alpha f(x+)+\beta f(x-) ,\quad x\in\mathbb{R}

Here, f(x+)f(x+) and f(x)f(x-) are respectively the upper and lower limits of ff at xx. Especially if ff is continuous at xx, the following equation holds.

limϵ0fgϵ(x)=f(x) \lim \limits_{\epsilon \to 0} f \ast g_{\epsilon}(x)=f(x)

Moreover, if ff 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.

limϵ0fgϵ(x)αf(x+)βf(x)=0 \lim \limits_{\epsilon \to 0} \left| f \ast g_{\epsilon}(x)-\alpha f(x+)-\beta f(x-) \right|=0

Arranging the inside of the absolute value gives the following.

fgϵ(x)αf(x+)βf(x)= f(xy)gϵ(y)dy0g(y)dyf(x+)0g(y)dyf(x)= f(xy)gϵ(y)dy0gϵ(y)dyf(x+)0gϵ(y)dyf(x)= 0[f(xy)f(x+)]gϵ(y)dy+0[f(xy)f(x)]gϵ(y)dy \begin{align} &f \ast g_{\epsilon}(x)-\alpha f(x+)-\beta f(x-) \nonumber \\ =&\ \int_{-\infty}^{\infty}f(x-y)g_{\epsilon}(y)dy- \int_{-\infty}^{0}g(y)dyf(x+)- \int_{0}^{\infty}g(y)dyf(x-) \nonumber \\ =&\ \int_{-\infty}^{\infty}f(x-y)g_{\epsilon}(y)dy- \int_{-\infty}^{0}g_{\epsilon}(y)dyf(x+)- \int_{0}^{\infty}g_{\epsilon}(y)dyf(x-) \nonumber \\ =&\ \int_{-\infty}^{0}\big[ f(x-y)-f(x+) \big]g_{\epsilon}(y)dy+\int_{0}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \label{eq1} \end{align}

Now, let’s suppose an arbitrary positive number δ>0\delta >0 is given. Then, due to the definition of lower and upper limits,

0<y<c    f(xy)f(x±)<δ \begin{equation} 0<y<c \implies \left| f(x-y)-f(x\pm) \right| <\delta \label{eq2} \end{equation}

there exists c>0c>0 that satisfies the condition. Now, let’s solely arrange the second term of (eq1)\eqref{eq1}. The integration interval can be divided as follows.

0[f(xy)f(x)]gϵ(y)dy= 0c[f(xy)f(x)]gϵ(y)dy+c[f(xy)f(x)]gϵ(y)dy \begin{align} &\int_{0}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \nonumber \\ =&\ \int_{0}^{c}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy+\int_{c}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \label{eq3} \end{align}

First, let’s investigate the first term of (eq3)\eqref{eq3}. From the condition (eq2)\eqref{eq2}, we can obtain the following equation.

0c[f(xy)f(x)]gϵ(y)dy<0cδgϵ(y)dy=δ0c/ϵg(y)dy \begin{align*} \left| \int_{0}^{c}\big[ f(x-y)-f(x-)\big]g_{\epsilon}(y)dy \right| &< \int_{0}^{c}\delta \left| g_{\epsilon}(y) \right|dy \\ &=\delta\int_{0}^{c/\epsilon} \left| g(y) \right|dy \end{align*}

Therefore,

limϵ00c[f(xy)f(x)]gϵ(y)dy=0 \begin{equation} \lim\limits_{\epsilon \to 0}\left| \int_{0}^{c}\big[ f(x-y)-f(x-)\big]g_{\epsilon}(y)dy \right|=0 \label{eq4} \end{equation}

The process of dealing with the remaining integration interval can be divided into two cases.

  • Case 1. If ff is bounded

    The second term of (eq3)\eqref{eq3} can be arranged as below due to the boundedness of ff. Let’s say it is fM\left| f \right| \le 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,

    limϵ0c[f(xy)f(x)]gϵ(y)dy=0 \begin{equation} \lim \limits_{\epsilon \to 0} \left| \int_{c}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \right| =0 \label{eq5} \end{equation}

  • Case 2. When x>a\left| x \right|>a for g(x)=0g(x)=0

    Then, whenever x>ϵa\left| x \right|>\epsilon a , we have gϵ(x)=0g_{\epsilon}(x)=0. Then for sufficiently small ϵ\epsilon,

    x>c    gϵ(x)=0 \left| x \right|>c \implies g_{\epsilon}(x)=0

    This holds. Therefore,

    limϵ0c[f(xy)f(x)]gϵ(y)dy=0 \begin{equation} \lim \limits_{\epsilon \to 0} \left| \int_{c}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \right| =0 \label{eq6} \end{equation}


Thus, from (eq3)\eqref{eq3}, (eq4)\eqref{eq4}, (eq5)\eqref{eq5}, and (eq6)\eqref{eq6}, we get the following result.

limϵ00[f(xy)f(x)]gϵ(y)dy=0 \lim \limits_{\epsilon \to 0}\left| \int_{0}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \right|=0

Applying the same method to the first term of (eq1)\eqref{eq1} gives us the next.

limϵ00[f(xy)f(x+)]gϵ(y)dy=0 \lim \limits_{\epsilon \to 0}\left| \int_{-\infty}^{0}\big[ f(x-y)-f(x+) \big] g_{\epsilon}(y)dy \right|=0

Therefore,

limϵ0fgϵ(x)αf(x+)βf(x)limϵ00[f(xy)f(x+)]gϵ(y)dy+limϵ00[f(xy)f(x)]gϵ(y)dy=0 \begin{align*} &\lim \limits_{\epsilon \to 0}\left| f \ast g_{\epsilon}(x)-\alpha f(x+)-\beta f(x-) \right| \\ \le& \lim \limits_{\epsilon \to 0}\left| \int_{-\infty}^{0}\big[ f(x-y)-f(x+) \big]g_{\epsilon}(y)dy \right| \\ &+\lim \limits_{\epsilon \to 0} \left| \int_{0}^{\infty}\big[ f(x-y)-f(x-) \big] g_{\epsilon}(y)dy \right| \\ &= 0 \end{align*}

Since this holds,

limϵ0fgϵ(x)=αf(x+)+βf(x),xR \lim \limits_{\epsilon \to 0}f \ast g_{\epsilon}(x)=\alpha f(x+)+\beta f(x-) ,\quad x\in\mathbb{R}

Also, if ff is continuous at xx, since f(x+)=f(x)f(x+)=f(x-) and α+β=1\alpha+\beta =1, then

limϵ0fgϵ(x)=f(x) \lim \limits_{\epsilon \to 0} f \ast g_{\epsilon}(x)=f(x)

At this point, a bounded closed interval is compact, and if ff is continuous on some compact set, it is uniformly continuous. Thus, in selecting cc above, it becomes independent of xx, which indicates that fgϵf \ast g_{\epsilon} converges uniformly to ff.