Aliasing: Boon or Bane
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
  
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