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== Example: Linear ==
 
== Example: Linear ==
  
 +
One-Way
  
 +
x1(t) -> [sys] -> y1(t) = cos(t) -> (X)*a +++
 +
                                a*cos(t)+b*sin(t) = z(t)
 +
x2(t) -> [sys] -> y2(t) = sin(t) -> (X)*b +++
  
  
 +
Reverse-Way
 +
 +
cos(t) = x1(t)*a +++
 +
                  a*cos(t)+b*sin(t) -> [sys] -> w(t)
 +
sin(t) = x2(t)*b +++
 +
 +
 +
since w(t) = z(t) then the inputs are the same as the outputs which makes this a linear system.
  
 
== Example: Non-Linear ==
 
== Example: Non-Linear ==

Revision as of 11:11, 12 September 2008

Linearity

So a system is linear if its inputs x1(t), x2(t) or (x1[n], x2[n] for Discrete Time signals) yield outputs y1(t), y2(t) such as the response: a*x1(t)+b*x2(t) => a*y1(t)+b*y2(t).


Example: Linear

One-Way

x1(t) -> [sys] -> y1(t) = cos(t) -> (X)*a +++

                                a*cos(t)+b*sin(t) = z(t)

x2(t) -> [sys] -> y2(t) = sin(t) -> (X)*b +++


Reverse-Way

cos(t) = x1(t)*a +++

                 a*cos(t)+b*sin(t) -> [sys] -> w(t)

sin(t) = x2(t)*b +++


since w(t) = z(t) then the inputs are the same as the outputs which makes this a linear system.

Example: Non-Linear

One-way


y[n] = 2*x[n]^3

x1[n] -> [sys] -> y1[n]=2*x1[n]^3 -> (X)*a +++

                                 = a*2*x1[n]^3+2*b*x2[n]^3

x2[n] -> [sys] -> y2[n]=2*x2[n]^3 -> (X)*b +++

Reverse-way


x1[n] -> (X)*a +++

             = a*x1[n]+b*x2[n] -> [sys] -> 2*z[n]^3 = 2*(a*x1[n] + b*x2[n])^3

x2[n] -> (X)*b +++


However, since 2*a*x1[n]^3 + 2*b*x2[n] != 2(a*x1[n] + b*x2[n])^3 = 8*a^3*x1[n]^3 + 8*b^3*x2[n]^3 the system is not linear because the two inflexive operations are not equal to each other.

Alumni Liaison

Ph.D. on Applied Mathematics in Aug 2007. Involved on applications of image super-resolution to electron microscopy

Francisco Blanco-Silva