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In linearity, the values are scalable and follow the rules of superposition.
 
In linearity, the values are scalable and follow the rules of superposition.
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==An example of a non-linear system==
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<math>y(t)=t^2*sqrt(x(t))</math>
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x1(t)-->system--> *A =x1'(t)
 +
x2(t)-->system--> *B =x2'(t)
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w(t)=x1'(t)+x2'(t)= <math>A*t^2*sqrt(x1(t))+B*t^2*sqrt(x2(t))</math>
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x3(t)--> *A -->system--> = x3'(t)
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x4(t)--> *B -->system--> = x4'(t)
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 +
z(t)=x3'(t) + x4'(t)= <math>t^2*sqrt(A*x1(t))+t^2*sqrt(B*x2(t))</math>
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Since z(t) is not equal to w(t) (because one equation has root A and root B and the other just has A and B) the system is non-linear.
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==An example of a linear system==
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 +
<math>y(t)=t^2*x(t)</math>
 +
 +
x1(t)-->system--> *A =x1'(t)
 +
x2(t)-->system--> *B =x2'(t)
 +
 +
w(t)=x1'(t)+x2'(t)= <math>A*t^2*x1(t)+B*t^2*x2(t)</math>
 +
 +
 +
x3(t)--> *A -->system--> = x3'(t)
 +
x4(t)--> *B -->system--> = x4'(t)
 +
 +
z(t)=x3'(t) + x4'(t)= <math>t^2*A*x1(t)+t^2*B*x2(t)</math>
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Since z(t) is equal to w(t) the system is linear.

Latest revision as of 12:20, 10 September 2008

Linearity

Because engineers talk in symbols instead of words...the following describes linearity.

  • A/*B = multiply by any complex number
x(t) --> system --> *A 
                     |
                     + --> w(t)
                     |
y(t) --> system --> *B 

x(t) --> *A 
          |
          + --> system --> z(t)
          |
y(t) --> *B 

If z(t) == w(t) then the system is linear.

In linearity, the values are scalable and follow the rules of superposition.

An example of a non-linear system

$ y(t)=t^2*sqrt(x(t)) $

x1(t)-->system--> *A =x1'(t) x2(t)-->system--> *B =x2'(t)

w(t)=x1'(t)+x2'(t)= $ A*t^2*sqrt(x1(t))+B*t^2*sqrt(x2(t)) $


x3(t)--> *A -->system--> = x3'(t) x4(t)--> *B -->system--> = x4'(t)

z(t)=x3'(t) + x4'(t)= $ t^2*sqrt(A*x1(t))+t^2*sqrt(B*x2(t)) $

Since z(t) is not equal to w(t) (because one equation has root A and root B and the other just has A and B) the system is non-linear.

An example of a linear system

$ y(t)=t^2*x(t) $

x1(t)-->system--> *A =x1'(t) x2(t)-->system--> *B =x2'(t)

w(t)=x1'(t)+x2'(t)= $ A*t^2*x1(t)+B*t^2*x2(t) $


x3(t)--> *A -->system--> = x3'(t) x4(t)--> *B -->system--> = x4'(t)

z(t)=x3'(t) + x4'(t)= $ t^2*A*x1(t)+t^2*B*x2(t) $

Since z(t) is equal to w(t) the system is linear.

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