Additive property:
If:
- x1(t)→y1(t)
- x2(t)→y2(t)
Then:
x1(t)+x2(t)→y1(t)+y2(t)
Scaling property:
If x1(t)→y1(t), then kx1(t)→ky2(t)
Additive + Scaling = Linear:
If:
- x1(t)→y1(t)
- x2(t)→y2(t)
Then:
k1x1(t)+k2x2(t)→k1y1(t)+k2y2(t)
Linear Example
Given y(t)=tx(t), we have:
x1(t)→y1(t)=tx1(t)x2(t)→y2(t)=tx2(t)
Then:
x3(t)=ax1(t)+bx2(t)→y3(t)=tx3(t)=t[ax1(t)+b(x2)t]=tax1(t)+tbx2(t)=ay1(t)+by2(t)∴ System is linear
Non-linear Example 1
Given a system of y(t)=x3(t), we have
x1(t)→y1(t)=x13(t)
Thus:
x2(t)=kx1(t)→y2(t)=x23(t)=(kx1(t))3=k3x13(t)=ky1(t)∴ Scaling doesn’t hold, non-linear
Non-linear Example 2
Given a system of y[n]=Re{x[n]}, such that:
x1[n]=δ1[n]+jω1[n]→y1[n]=δ1[n]
However, let’s say that x2[n] is defined to be jx1[n], we would have:
x2[n]=jx1[n]=jδ1[n]−ω1[n]→y2[n]=−ω1[n]
so y2[n]=jy1[n], failing the scaling property, making the system nonlinear.