Fourier Series

Definition

Exponential Form

Let x(t) be a complex-valued periodic signal with period T>0 and angular frequency ω0=2πT. Then,

x~(t)=n=Xnejnω0t

where,

Xn=1TT2T2x(t)ejnω0tdt

and x~(t) is the Fourier Series of x(t).

Special Case for Real Periodic Signals

Let x(t) be a real-valued periodic signal with period T>0 and angular frequency ω0=2πT. Then,

x~(t)=X0+2n=1Re(Xnejnω0t)

where,

Xn=1TT2T2x(t)ejnω0tdt

and x~(t) is the Fourier Series of x(t).

Trigonometric Form

Let x(t) be a complex-valued periodic signal with period T>0 and angular frequency ω0=2πT. Then,

x~(t)=12a0+n=1(ancos(nω0t)+bnsin(nω0t))x~(t)=12a0+n=1(ancos(2πnf0t)+bnsin(2πnf0t))

where,

a0=1TTx(t)dtan=2TTx(t)cos(nω0t)dt=2TTx(t)cos(2πnf0t)dtbn=2TTx(t)sin(nω0t)dt=2TTx(t)sin(2πnf0t)dt

and x~(t) is the Fourier Series of x(t).

Fourier Transform

Definition

Let x(t) be a complex-valued signal and ω=2πf. Then,

F{x(t)}=X(ω)=x(t)ejωtdt,forall<ω<F{x(t)}=X(f)=x(t)ej2πftdt,forall<f<

and,

x(t)=12πX(ω)ejωtdω,forall<t<x(t)=X(f)ej2πftdf,forall<t<

where F{x(t)}=X(ω) and F{x(t)}=X(f) are Fourier Transforms of x(t).

Properties

Linearity

Duality

Complex Conjugate

Symmetry

Time Scaling

Time Shift

Frequency Shift

Derivatives

Integrals

Convolution

Multiplication

Multiplication by t

Parseval's Theorem

Fourier Transform Table

Signal x(t) for t0Fourier Transform X(ω)Fourier Transform X(f)
δ(t)11
12πδ(ω)δ(f)
δ(tt0)ejωt0ej2πft0
cos(ω0t),cos(2πf0t)π[δ(ωω0)+δ(ω+ω0)]12[δ(ff0)+δ(f+f0)]
sin(ω0t),sin(2πf0t)jπ[δ(ωω0)δ(ω+ω0)]12j[δ(ff0)δ(f+f0)]
u(t)πδ(ω)+1jω12δ(f)+1j2πf
(t)πsinc(ω2π)*sinc(f)*
Λ(t)π2sinc2(ω2π)*sinc2(f)*
sgn(t)2jω1jπf
eαtu(t),[α>0]1α+jω1α+j2πf
eαtu(t),[α>0]1αjω1αj2πf
eα|t|,[α>0]2αα2+ω22αα2+(2πf)2
eαt2παeω24απαe(2πf)24α
teαtu(t),[α>0]1(α+jω)21(α+j2πf)2
tneαtu(t),[α>0]n!(α+jω)n+1n!(α+j2πft)n+1
n=δ(tnT0)ω0n=δ(ωnω0)f0n=δ(fnf0)

*sinc(t)=sin(πt)πt