Aliasing: Boon or Bane

Lecture 7: Digital Signal What?

22/10/2004
Summary:
  • Aliasing - if a spiral moves more than half a circle in one sample, it seems as if it is a slower spiral (village chief's cow)
  • Sampling
    • Sampling should be faster than twice the highest frequency - Nyquist theorem
    • Analog filtering before ADC necessary to avoid aliasing
  • Periodic signals
    • Filtering of periodic signal gives periodic signal
    • This can be calculated using circular convolution (circular domain - signal wrapped around on itself)
    • If the filter kernel is larger than period, the filter kernel can be wrapped around on itself and made circular
    • For periodic signal, only spirals of that period (harmonic spirals) are important
    • This harmonicity and aliasing together means a finitely many spirals are to be used - DFT
  • Derivative
    • Derivative is the most basic LTI operator in continuous domain
    • Relation between step response and impulse response
  • Unit shift
    • Most basic discrete domain LTI operator is unit delay
    • Unit delay causes linear phase change in spirals
    • The linear phase shift is the frequency response of the unit delayer
    • Can be composed to get multiple sample shify
  • If a signal is "stretched" by putting in alternate zeros, the Fourier transform gets repeated twice
    • The spiral and its high frequency alias look the same at the points that matter
    • The spiral and its high frequency alias cancel at the points which don't matter
  • The stretch and shift theorems and linearity together give the fast Fourier transform (FFT) -
    • decimate the signal into two signals
    • recursively compute their Fourier transforms
    • stretch these two signals = duplicate their Fourier transforms
    • shift the "odd" signal = linear phase shift in Fourier transform
    • add the two signals = add the Fourier transforms
  • The FFT runs in order of n log n time
  • FFT is used to implement circular convolution
    • transform the signal and the filter
    • multiply the transforms point-wise
    • transform the result back
  • Circular convolution is used to implement linear convolution