I Partial Derivative of Convolution

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The discussion focuses on calculating the partial derivative of a convolution where only one function, y(t, r), depends on the variable r. The user initially references a known identity for derivatives of convolutions when both functions depend on the same variable. After clarification, it is established that the partial derivative can be computed using the integral form of convolution. The resulting expression shows that the partial derivative with respect to r can be expressed as the convolution of x(t) with the partial derivative of y(t, r). This approach provides a clear method for handling partial derivatives in convolutions involving multiple variables.
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Calculating the partial derivative of a convolution
Hello, I am trying to calculate the partial derivative of a convolution. This is the expression:
##\frac{\partial}{\partial r}(x(t) * y(t, r))##​

Only y in the convolution depends on r. I know this identity below for taking the derivative of a convolution with both of the functions only depending on t:
##\frac{d}{dt}(x(t)*y(t) = (\frac{dx(t)}{dt}*y(t)) = (x(t)*\frac{dy(t)}{dt})##​

I'm not sure how this changes when taking a partial derivative with only one of the functions depending on the variable that the partial derivative is being taken with respect to. Any help/resources would be appreciated! (This is my first post here, please let me know if I need to improve my post formatting/structure).
 
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Your convolution is (x * y)(t,r)=\int_{-\infty}^{\infty} x(\tau)y(t - \tau, r)\,d\tau, is it not? What happens if you differentiate that with respect to r?
 
Ah thanks, I think I see what you mean:
##\frac{\partial}{\partial r} (x * y)(t,r) = \int_{-\infty}^{\infty} x(\tau)\frac{\partial}{\partial r}y(t - \tau, r)d\tau = (x*\frac{\partial y}{\partial r})(t,r)##​
 

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