(Linear Systems)
(Linear Systems)
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Because we are engineers we will use a picture to describe a linear system:
 
Because we are engineers we will use a picture to describe a linear system:
  
[[Image:Systempjcannon_ECE301Fall2008mboutin.JPG]]
+
[[Image:Systempjcannon2_ECE301Fall2008mboutin.JPG]]
  
 
Where <math>a \!</math> and <math>b\!</math> are real or complex.  The system is defined as linear if <math>z(t)=w(t)\!</math>
 
Where <math>a \!</math> and <math>b\!</math> are real or complex.  The system is defined as linear if <math>z(t)=w(t)\!</math>
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<br>
 
<br>
 
In other words, if in one scenario we have two signals put into a system, multiplied by a variable, then summed together, the output should equal the output of a second scenario where the signals are multiplied by a variable, summed together, then put through the same system.  If this is true, then the system is defined as linear.
 
In other words, if in one scenario we have two signals put into a system, multiplied by a variable, then summed together, the output should equal the output of a second scenario where the signals are multiplied by a variable, summed together, then put through the same system.  If this is true, then the system is defined as linear.
 
  
 
== Example of a Linear System ==
 
== Example of a Linear System ==
 
Let <math>y(t)=x(t) \!</math>.  Then:
 
Let <math>y(t)=x(t) \!</math>.  Then:

Revision as of 11:25, 11 September 2008

Linear Systems

Because we are engineers we will use a picture to describe a linear system:

Systempjcannon2 ECE301Fall2008mboutin.JPG

Where $ a \! $ and $ b\! $ are real or complex. The system is defined as linear if $ z(t)=w(t)\! $

In other words, if in one scenario we have two signals put into a system, multiplied by a variable, then summed together, the output should equal the output of a second scenario where the signals are multiplied by a variable, summed together, then put through the same system. If this is true, then the system is defined as linear.

Example of a Linear System

Let $ y(t)=x(t) \! $. Then:

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Sees the importance of signal filtering in medical imaging

Dhruv Lamba, BSEE2010