10/10,13,16,17 - Fourier Transform Properties

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Properties of the Fourier Transform

Linearity

F[ax(t)+bx(t)] =[ax(t)+bx(t)]ej2πftdt
=ax(t)ej2πftdt+bx(t)ej2πftdt
=aF[x(t)]+bF[x(t)]

Time Invariance (Delay)

F[x(tt0)] =x(tt0)ej2πftdt Let u=tt0 and du=dt
=x(u)ej2πf(u+t0)du
=ej2πft0x(u)ej2πfudu
=ej2πft0F[x(t)]

Frequency Shifting

F[ej2πftx(t)] =[ej2πf0tx(t)]ej2πftdt
=x(t)ej2π(ff0)tdt
=X(ff0)

Double Sideband Modulation

F[cos(2πf0t)x(t)] =ej2πf0t+ej2πf0t2x(t)ej2πftdt
=12x(t)[ej2π(ff0)t+ej2π(f+f0)t]dt
=12X(ff0)+12X(f+f0)

Differentiation in Time

x(t) =F1[X(f)]
F[dxdt] =F[ddtF1[X(f)]]
=F[ddtX(f)ej2πftdf]
=F[j2πfX(f)ej2πftdf]
=F[j2πfF1[X(f)]]
=j2πfX(f) Thus dxdt is a linear filter with transfer function j2πf

The Game (frequency domain)

  • You can play the game in the frequency or time domain, but not both at the same time
    • Then how can you use the Fourier Transform, but can't build up to it?
Input LTI System Output Reason
δ(t) h(t) Given
δ(t)ej2πft h(t)ej2πft Proportionality
δ(t)ej2πftdt=F[δ(t)]=1 h(t)ej2πftdt=F[h(t)]=H(f) Superposition
δ(tλ)ej2πftdt=F[δ(tλ)]=1ej2πfλ H(f)ej2πfλ Time Invariance
x(λ)1ej2πfλ x(λ)H(f)ej2πfλ Proportionality
x(λ)1ej2πfλdλ=X(f) x(λ)H(f)ej2πfλdλ=X(f)H(f) Superposition
  • Having trouble seeing F[x(t)*h(t)]=X(f)H(f)
  • Since we were dealing in the frequency domain, is that the reason why multiplying one side did not result in a convolution on the other?

The Game (Time Domain??)

Input LTI System Output Reason
1ej2πf0t h(t)*ej2πf0t=ej2πf0t*h(t) Proportionality
h(λ)ej2πf0(tλ)dλ Why d lambda instead of dt?
ej2πf0λh(λ)ej2πf0λdλ
ej2πf0tH(f0)
X(f0)ej2πf0t X(f0)ej2πf0tH(f0) Proportionality, Why isn't this a convolution?
X(f0)ej2πf0tdf0=x(t) X(f0)H(f0)ej2πf0tdf0=F1[X(f)H(f)] Superposition, Not X(f_0)H(f_0)?


Relation to the Fourier Series

x(t) =x(t+T)
=n=αnej2πnt/T
=m=1αmej2πmt/TNegativefrequencies+α0+n=1αnej2πnt/T
=n=1αnej2πnt/T+α0+n=1αnej2πnt/T Let n=m and reverse the order of summation
Note that αnej2πnt/T is the complex conjugate of αnej2πnt/T
=α0+2[n=1αnej2πnt/T] x(t)+x(t)*=2[x(t)]
  • How can we assume that the answer exists in the real domain? You can break any function down into a Taylor series. There are even and odd powers in the series.

Remember from 10/02 - Fourier Series that αn=1TT/2T/2x(t)ej2πnt/Tdt

  • αn=|αn|ejθ?
  • Rest of page

Building up to F[u(t)]

eiπ =cosπ+isinπ. Euler's Identity
r0(t) =r0(t) Real odd function of t
F[r0(t)] =r0(t)ej2πftdt
=r0(t)[cos(2πft)+jsin(2πft)]dt
=r0(t)[cos(2πft)jsin(2πft)]dt cos(x)=cos(x) & sin(x)=sin(x)
=jr0(t)sin(2πft)dt r0(t)jsin(2πft) = Real odd. Integrates out over symmetric limits.
=Imaginary Odd function of f
re(t) =re(t) Real even function of t
F[re(t)] =re(t)ej2πftdt
=re(t)[cos(2πft)+jsin(2πft)]dt
=re(t)[cos(2πft)jsin(2πft)]dt cos(x)=cos(x) & sin(x)=sin(x)
=re(t)cos(2πft)dt re(t)cos(2πft) = Real odd. Integrates out over symmetric limits.
=Real Even function of f

Definitions

x(t) =xe(t)+x(o)t Can't x(t) have parts that aren't even or odd?
xe(t) =x(t)+x(t)2
xo(t) =x(t)x(t)2
u(t) =1+sgn(t)2 sgn(t)={1,t>00,t=01,t<0
ue(t) =12
uo(t) =sgn(t)2


F[u(t)]

F[12] =12ej2πftdt
=12δ(f)
F[sgn(t)2] =sgn(t)2ej2πftdt
=12[01ej2πftdt+01ej2πftdt]
=120ej2πfuduu=tdu=dt+120ej2πfuduu=tdu=dt
=0ej2πfu+ej2πfu2du
=0cos(2πfu)du