Line 13: Line 13:
  
 
One-way
 
One-way
 +
 +
 
y[n] = 2*x[n]^3
 
y[n] = 2*x[n]^3
  
Line 20: Line 22:
  
 
Reverse-way
 
Reverse-way
 +
  
 
x1[n] -> (X)*a +++
 
x1[n] -> (X)*a +++
               a*x1[n]+b*x2[n] -> [sys] -> 2*z[n]^3 = 2*(a*x1[n] + b*x2[n])^3
+
               = a*x1[n]+b*x2[n] -> [sys] -> 2*z[n]^3 = 2*(a*x1[n] + b*x2[n])^3
 
x2[n] -> (X)*b +++
 
x2[n] -> (X)*b +++

Revision as of 08:10, 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

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 +++

Alumni Liaison

Correspondence Chess Grandmaster and Purdue Alumni

Prof. Dan Fleetwood