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    Nontechnical description of Fourier transform
  2. Урок 2.00:11:50
    Examples of Fourier transform applications
  3. Урок 3.00:03:16
    MATLAB, Octave, Python, or just watch
  4. Урок 4.00:03:46
    Leaving reviews, course coupons
  5. Урок 5.00:14:06
    Complex numbers
  6. Урок 6.00:09:33
    Euler's formula e^ik
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    Sine waves and complex sine waves
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    Dot product
  9. Урок 9.00:09:06
    Complex dot product
  10. Урок 10.00:12:12
    How the discrete Fourier transform works
  11. Урок 11.00:08:39
    Converting indices to frequencies
  12. Урок 12.00:09:34
    Normalized time vector
  13. Урок 13.00:04:51
    Positive and negative frequencies
  14. Урок 14.00:06:31
    Accurate scaling of Fourier coefficients
  15. Урок 15.00:05:11
    Interpreting phase values
  16. Урок 16.00:09:01
    Averaging Fourier coefficients
  17. Урок 17.00:07:43
    The DC (zero frequency) component
  18. Урок 18.00:06:51
    Amplitude spectrum vs. power spectrum
  19. Урок 19.00:05:06
    A note about terminology of Fourier features
  20. Урок 20.00:10:49
    How and why it works
  21. Урок 21.00:07:22
    Inverse Fourier transform for bandstop filtering
  22. Урок 22.00:07:12
    How it works, speed tests
  23. Урок 23.00:02:11
    The fast inverse Fourier transform
  24. Урок 24.00:06:50
    The perfection of the Fourier transform
  25. Урок 25.00:07:25
    Using the fft on matrices
  26. Урок 26.00:16:21
    Sampling and frequency resolution
  27. Урок 27.00:11:14
    Time-domain zero padding
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    Frequency-domain zero padding
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    Sampling rate vs. signal length
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    Aliasing
  31. Урок 31.00:05:40
    Signal stationarity and non-stationarities
  32. Урок 32.00:16:00
    Effects of non-stationarities on the power spectrum
  33. Урок 33.00:13:10
    Solution to understanding nonstationary time series
  34. Урок 34.00:09:51
    Windowing and Welch's method
  35. Урок 35.00:11:34
    Instantaneous frequency
  36. Урок 36.00:11:14
    How the 2D FFT works
  37. Урок 37.00:06:07
    Rhythmicity in walking (gait)
  38. Урок 38.00:07:04
    Rhythmicity in electrical brain waves
  39. Урок 39.00:03:13
    Time series convolution
  40. Урок 40.00:08:16
    Narrowband temporal filtering
  41. Урок 41.00:07:32
    2D image filtering
  42. Урок 42.00:05:55
    Image narrowband filtering
  43. Урок 43.00:04:12
    Real data from trends.google.com!