If the signal $x(t)$ has ordinary first derivative $\dot x(t)$, then $\dfrac{d}{dt}\big(x(t)\star y(t)\big)$ is:
- (a) $\dot x(t)y(t)$
- (b) $x(t)\dot y(t)$
- (c) $\dot x(t)\star y(t)$
- (d) $\dot x(t)\star \dot y(t)$
I solved it as follows: we know,
$$I(t)=x(t)\star y(t)=\displaystyle\int_{-\infty}^{\infty}x(\tau).y(t-\tau) d{\tau}\implies$$ $$\begin{align}\dfrac{dI(t)}{dt}&=\dfrac{d}{dt}\displaystyle\int_{-\infty}^{\infty}x(\tau)y(t-\tau) d{\tau}\\&=\displaystyle\int_{-\infty}^{\infty}\dfrac{\partial}{\partial t}x(\tau).y(t-\tau) d{\tau} \\&=\displaystyle\int_{-\infty}^{\infty}x(\tau).\dfrac{\partial}{\partial t}y(t-\tau) d{\tau}=x(t)\star \dot y(t)\end{align}$$
So option $(b)$ should be correct but answer in the book is given as $(c)$ but I think both options $(b)$ and $(c)$ should be correct because in above method I fixed $x(t)$ and shifted $y(t)$ but we can also do that other way round fixing $y(t)$ and shifting $x(t)$,and we know by doing so,convolution integral remain unaffected,so tell where i'm wrong ,any help would be appreciated