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We are given the input to an LTI system along with the system's impulse response and told to find the output y(t).  Since the input and impulse response are given, we simply use convolution on x(t) and h(t) to find the system's output.
 
We are given the input to an LTI system along with the system's impulse response and told to find the output y(t).  Since the input and impulse response are given, we simply use convolution on x(t) and h(t) to find the system's output.
  
  <math>y(t) = h(t) * x(t) = \int_{-\infty}^\infty h(t-\tau)x(t)d\tau</math>  COMMUTATIVE PROPERTY
+
  <math>y(t) = h(t) * x(t) = \int_{-\infty}^\infty h(t-\tau)x(t)d\tau</math>  ('''COMMUTATIVE PROPERTY'''''Italic text'')
  
  

Revision as of 16:33, 30 June 2008

We are given the input to an LTI system along with the system's impulse response and told to find the output y(t). Since the input and impulse response are given, we simply use convolution on x(t) and h(t) to find the system's output.

$ y(t) = h(t) * x(t) = \int_{-\infty}^\infty h(t-\tau)x(t)d\tau $  (COMMUTATIVE PROPERTYItalic text)


Plugging in the given x(t) and h(t) values results in:

$ \begin{align} y(t) & = \int_{-\infty}^\infty e^{-t-\tau}u(t-\tau)u(\tau-1)d\tau \\ & = \int_1^\infty e^{-t-\tau}u(t-\tau)d\tau \\ & = \int_1^{t} e^{-t-\tau}d\tau \\ & = e^{-t}\int_1^{t} e^{\tau}d\tau \\ & = e^{-t}(e^{t} - e) \\ & = 1-e^{-(t-1)}\, \mbox{ for } t > 1 \end{align} $


Since x(t) = 0 when t < 1:

$ y(t) = 0\, \mbox{ for } t < 1 $


$ \therefore y(t) = \begin{cases} 1-e^{-(t-1)}, & \mbox{if }t\mbox{ is} > 1 \\ 0, & \mbox{if }t\mbox{ is} < 1 \end{cases} $

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood