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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 15:33, 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} $

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BSEE 2004, current Ph.D. student researching signal and image processing.

Landis Huffman