Line 7: Line 7:
 
<math>
 
<math>
 
   h(t) = \left\{
 
   h(t) = \left\{
   \begin{array}{11}
+
   \begin{array}{lr}
       \mathrm{e}^{-t} & \mbox{: t \geq 0}\\
+
       \mathrm{e}^{-t} & : t \geq 0\\
       0              & \mbox{ : t < 0}
+
       0              & : t < 0
 
     \end{array}
 
     \end{array}
 
   \right.
 
   \right.

Revision as of 18:39, 10 February 2013

Convolution is often presented in a manner that emphasizes efficient calculation over comprehension of the convolution itself. To calculate in a pointwise fashion, we're told: "flip one of the input signals, and perform shift+multiply+add operations until the signals no longer overlap." This is numerically valid, but to emphasize that the convolution represents a summation of impulse responses generated by the input signal over time, here I will present a less compact but hopefully more illustrative approach to compute the following:

$ x(t) \conv h(t) $

$ x(t) \,=\, 1 \;\;\;\;\; \forall \, t $

$ h(t) = \left\{ \begin{array}{lr} \mathrm{e}^{-t} & : t \geq 0\\ 0 & : t < 0 \end{array} \right. $


$ \int_{-\infty}^{\infty} h(\tau)\,\mathrm{d}\tau \,=\, \int_{0}^{\infty} h(\tau)\,\mathrm{d}\tau \;\;\;\;\; \because h(t)=0 \;\;\; \forall \, t<0 $

$ \Rightarrow \int_{0}^{\infty} \mathrm{e}^{-\tau}\,\mathrm{d}\tau \,=\, \left.-\mathrm{e}^{-\tau}\right|_{0}^{\infty} \,=\, -(\mathrm{e}^{-\infty} - \mathrm{e}^{0}) \,=\, -(0 - 1) \,=\, 1 $


$ \int_{-\infty}^{\infty} h(t-\tau)\,\mathrm{d}\tau \,=\, \int_{-\infty}^{t} h(t-\tau)\,\mathrm{d}\tau \;\;\;\;\; \because h(t)=0 \;\;\; \forall \, t<0 $

$ \Rightarrow \int_{-\infty}^{t} \mathrm{e}^{-(t-\tau)}\,\mathrm{d}\tau \,=\, \int_{-\infty}^{t} \mathrm{e}^{\tau-t}\,\mathrm{d}\tau \,=\, \left.\mathrm{e}^{\tau-t}\right|_{-\infty}^{t} \,=\, \mathrm{e}^{0} - \mathrm{e}^{-\infty-t} \;\; (\forall \, t>0) \,=\, 1 - 0 \,=\, 1 $

Alumni Liaison

Ph.D. 2007, working on developing cool imaging technologies for digital cameras, camera phones, and video surveillance cameras.

Buyue Zhang