Signals and systems/GF Fourier: Difference between revisions

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<math> \alpha_m = \frac{1}{T}\int_{-T/2}^{T/2} x(t) e^{{-j2\pi mt}/T} dt </math>
<math> \alpha_m = \frac{1}{T}\int_{-T/2}^{T/2} x(t) e^{{-j2\pi mt}/T} dt </math>


== <math> \left \langle \ Bra \mid Ket \ \right \rangle </math> Notation ==


<math> \left \langle \ n \mid m \ \right \rangle = m \cdot n </math>


==Linear Time Invariant Systems==
==Linear Time Invariant Systems==

Revision as of 22:53, 29 October 2006

Fourier series

The Fourier series is used to analyze arbitrary periodic functions by showing them as a composite of sines and cosines.

A function is considered periodic if x(t)=x(t+T) for T0.

The exponential form of the Fourier series is defined as x(t)=n=αnej2πnt/T

Determining the coefficient αn

x(t)=n=αnej2πnt/T

  • The definition of the Fourier series

T/2T/2x(t)dt=n=αnT/2T/2ej2πnt/Tdt

  • Integrating both sides for one period. The range of integration is arbitrary, but using T/2T/2 scales nicely when extending the Fourier series to a non-periodic function

T/2T/2x(t)ej2πmt/Tdt=n=αnT/2T/2ej2πnt/Tej2πmt/Tdt=n=αnT/2T/2ej2π(nm)t/Tdt

  • Multiply by the complex conjugate

T/2T/2x(t)ej2πmt/Tdt=n=αnTej2π(nm)t/Tj2π(nm)|T/2T/2=n=αnTδn,m=Tαm

  • Tej2π(nm)t/Tj2π(nm)|T/2T/2=Tejπ(nm)ejπ(nm)j2π(nm)=Tsinπ(nm)π(nm)={T,n=m0,nm}=Tδn,m
    • Using L'Hopitals to evaluate the T00 case. Note that n & m are integers

αm=1TT/2T/2x(t)ej2πmt/Tdt


Linear Time Invariant Systems

Must meet the following criteria

  • Time independance
  • Linearity
    • Superposition (additivity)
    • Scaling (homogeneity)

Complex Conjugate

Changing Basis Functions

Identities

ejθ=cosθ+jsinθ

sinx=ejxejx2j

cosx=ejx+ejx2

BraKet=KetBra