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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'''''Italic text'')
+
  <math>y(t) = h(t) * x(t) = \int_{-\infty}^\infty h(t-\tau)x(t)d\tau</math>  ('''''COMMUTATIVE PROPERTY''''')
  
  
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<math>
 
<math>
 
\begin{align}
 
\begin{align}
  y(t) & = \int_{-\infty}^\infty e^{-t-\tau}u(t-\tau)u(\tau-1)d\tau \\
+
  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^\infty e^{-(t-\tau)}u(t-\tau)d\tau \\
       & = \int_1^{t} e^{-t-\tau}d\tau  \\  
+
       & = \int_1^{t} e^{-(t-\tau)}d\tau  \\  
 
       & = e^{-t}\int_1^{t} e^{\tau}d\tau  \\  
 
       & = e^{-t}\int_1^{t} e^{\tau}d\tau  \\  
 
       & = e^{-t}(e^{t} - e) \\
 
       & = e^{-t}(e^{t} - e) \\

Latest revision as of 15:56, 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 PROPERTY)


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

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

Buyue Zhang