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FOURIER ANALYSIS PART 2: Technicalities, FFT

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Title: FOURIER ANALYSIS PART 2: Technicalities, FFT


1
FOURIER ANALYSISPART 2 Technicalities, FFT
system analysis
  • Maria Elena Angoletta
  • AB/BDI
  • DISP 2003, 27 February 2003

2
TOPICS
  • 1. DFT windows
  • 2. DFT resolution - improvement
  • 3. Efficient DFT calculation FFT
  • 4. Hints on system spectral analysis

3
DFT Window characteristics
  • Finite discrete sequence ? spectrum convoluted
    with rectangular window spectrum.
  • Leakage amount depends on chosen window on how
    signal fits into the window.

4
DFT of main windows
Windowing reduces leakage by minimising sidelobes
magnitude.
5
DFT - Window choice
Common windows characteristics
NB Strong DC component can shadow nearby small
signals. Remove it!
6
DFT - Window loss remedial
Smooth data-tapering windows cause information
loss near edges.
  • Attenuated inputs get next windows full gain
    leakage reduced.
  • Usually 50 or 75 overlap (depends on main lobe
    width).

Drawback increased total processing time.
7
Zero padding
Improves DFT frequency inter-sampling spacing
(resolution).
8
Zero padding -2
DFT spectral resolution
9
DFT - scalloping loss (SL)
Input frequency f0 btwn. bin centres causes
magnitude loss
Worst case when f0 falls exactly midway between 2
successive bins (r½)
r ? ½
f0 (kmax r) fS/N
Frequency error ?f r fS/N, relative error
?R?f / f0 r/(kmaxr) ?R ? 1/(12 kmax)
kmax
f0
Note Non-rectangular windows broaden DFT main
lobe ? SL less severe Correction depends on
window used.
10
DFT - SL Example
DC bias correction, Rectang. window, zero
padding, FFT
DC bias correction, Hanning window, zero
padding, FFT
11
DFT - parabolic interpolation
Rectangular window
Hanning window
  • Parabolic interpolation often enough to find
    position of peak (i.e. frequency).
  • Other algorithms available depending on data.

12
DFT averaging
13
Efficient DFT calculation FFT
VERY BAD !
Algorithms ( Fast Fourier Transform) developed
to compute N-points DFT with Nlog2N
multiplications (complexity O(Nlog2N) ).
14
FFT advantages
NB Usually you dont want to write an FFT
algorithm, just to borrow it !!! Go
shopping onto the web!
15
FFT philosophy
General philosophy (to be applied recursively)
divide conquer.
Step 2 1-point input spectra calculation.
(Nothing to do!)
Step 3 Frequency-domain synthesis.
N spectra synthesised into one.
16
FFT family tree
Divide conquer
17
(Some) FFT concepts notes
18
Systems spectral analysis (hints)
System analysis measure input-output
relationship.
yn predicted from xn, ht
H(f) LTI transfer function
19
Estimating H(f) (hints)
20
References - 1
Papers
  • Tom, Dick and Mary discover the DFT, J. R. Deller
    Jr, IEEE Signal Processing Magazine, pg 36 - 50,
    April 1994.
  • On the use of windows for harmonic analysis with
    the Discrete Fourier Transform, F. J. Harris,
    IEEE Proceedings, Vol. 66, No 1, January 1978.
  • Some windows with a very good sidelobe behaviour,
    A. H. Nuttall, IEEE Trans. on acoustics, speech
    and signal processing, Vol ASSP-29, no. 1,
    February 1981.
  • Some novel windows and a concise tutorial
    comparison of windows families, N. C. Geckinli,
    D. Yavuz, IEEE Trans. on acoustics, speech and
    signal processing, Vol ASSP-26, no. 6, December
    1978.
  • Study of the accuracy and computation time
    requirements of a FFT-based measurement of the
    frequency, amplitude and phase of betatron
    oscillations in LEP, H.J. Schmickler, LEP/BI/Note
    87-10.
  • Causes et corrections des erreurs dans la mesure
    des caracteristiques des oscillations
    betatroniques obtenues a partir dune
    transformation de Fourier, E. Asseo, CERN PS 85-9
    (LEA).

21
References - 2
  • Precise measurements of the betatron tune, R.
    Bartolini et al., Particle Accel., 1996, vol. 55,
    pp 247-256.
  • How the FFT gained acceptance, J. W. Cooley, IEEE
    Signal Processing Magazine, January 1992.
  • A comparative analysis of FFT algorithms, A.
    Ganapathiraju et al., IEEE Trans.on Signal
    Processing, December 1997.

Books
  • The Fourier Transform and its applications, R. N.
    Bracewell, McGraw-Hill, 1986.
  • A History of scientific computing, edited by S.
    G. Nash, ACM Press, 1990.
  • Introduction to Fourier analysis, N. Morrison,
    John Wiley Sons, 1994.
  • The DFT An owners manual for the Discrete
    Fourier Transform, W. L. Briggs, SIAM, 1995.
  • The FFT Fundamentals and concepts, R. W.
    Ramirez, Prentice Hall, 1985.
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