(New page: == Linear System == For a function y=f(x), if its derivitive is a constant, then we say it is a linear system. == Example ==)
 
(Example)
 
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== Linear System ==
 
== Linear System ==
  
For a function y=f(x), if its derivitive is a constant, then we say it is a linear system.
+
A system is called "Linear"
 
+
if for any constants a,b and for any inputs x1(t),x2(t),(x1[n],x2[n])
 +
yielding output y1(t),y2(t),respectively, the respond to a*x1(t)+b*x2(t) is a*y1(t)+b*y2(t)
  
 
== Example ==
 
== Example ==
 +
A)LINEAR
 +
  Let:
 +
    x1(t)=t, x2(t)=2t; 
 +
    System: y(t)=3*x(t)
 +
    Thus, y1(t)=3t,y2(t)=6t
 +
  So say a,b are any non-zero constant
 +
    a*x1(t)->system->3at
 +
                        +    --->Output= 3at+6bt    -----(1)
 +
    b*x2(t)->system->6bt 
 +
 +
 +
    a*x1(t)+b*x2(t)=at+2bt->system->Output=3*(at+2bt)= 3at+6bt ----------(2)
 +
 +
    (1)=(2),so linear.
 +
 +
B)NON-LINEAR
 +
  Let:
 +
    x1(t)=t, x2(t)=2t; 
 +
    System: y(t)=x(t)^2
 +
    Thus, y1(t)=t^2,y2(t)=4t^2
 +
 +
  So say a,b are any non-zero constant
 +
    a*x1(t)->system->a*t^2
 +
                            +    --->Output= a*t^2+4b*t^2    -----(3)
 +
    b*x2(t)->system->b*4t^2
 +
 +
    a*x1(t)+b*x2(t)=at+2bt->system->Output=(at+2bt)^2 ----------(4)
 +
 +
    (3)!=(4),so non-linear.

Latest revision as of 17:02, 12 September 2008

Linear System

A system is called "Linear" if for any constants a,b and for any inputs x1(t),x2(t),(x1[n],x2[n]) yielding output y1(t),y2(t),respectively, the respond to a*x1(t)+b*x2(t) is a*y1(t)+b*y2(t)

Example

A)LINEAR

 Let:
    x1(t)=t, x2(t)=2t;   
    System: y(t)=3*x(t)
    Thus, y1(t)=3t,y2(t)=6t
 So say a,b are any non-zero constant
    a*x1(t)->system->3at
                       +    --->Output= 3at+6bt     -----(1)
    b*x2(t)->system->6bt  


    a*x1(t)+b*x2(t)=at+2bt->system->Output=3*(at+2bt)= 3at+6bt ----------(2)
    (1)=(2),so linear.

B)NON-LINEAR

 Let:
    x1(t)=t, x2(t)=2t;   
    System: y(t)=x(t)^2
    Thus, y1(t)=t^2,y2(t)=4t^2
 So say a,b are any non-zero constant
    a*x1(t)->system->a*t^2
                           +    --->Output= a*t^2+4b*t^2     -----(3)
    b*x2(t)->system->b*4t^2
    a*x1(t)+b*x2(t)=at+2bt->system->Output=(at+2bt)^2 ----------(4)
    (3)!=(4),so non-linear.

Alumni Liaison

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

Francisco Blanco-Silva