• Урок 1. 00:06:37
    Nontechnical description of Fourier transform
  • Урок 2. 00:11:50
    Examples of Fourier transform applications
  • Урок 3. 00:03:16
    MATLAB, Octave, Python, or just watch
  • Урок 4. 00:03:46
    Leaving reviews, course coupons
  • Урок 5. 00:14:06
    Complex numbers
  • Урок 6. 00:09:33
    Euler's formula e^ik
  • Урок 7. 00:14:01
    Sine waves and complex sine waves
  • Урок 8. 00:16:32
    Dot product
  • Урок 9. 00:09:06
    Complex dot product
  • Урок 10. 00:12:12
    How the discrete Fourier transform works
  • Урок 11. 00:08:39
    Converting indices to frequencies
  • Урок 12. 00:09:34
    Normalized time vector
  • Урок 13. 00:04:51
    Positive and negative frequencies
  • Урок 14. 00:06:31
    Accurate scaling of Fourier coefficients
  • Урок 15. 00:05:11
    Interpreting phase values
  • Урок 16. 00:09:01
    Averaging Fourier coefficients
  • Урок 17. 00:07:43
    The DC (zero frequency) component
  • Урок 18. 00:06:51
    Amplitude spectrum vs. power spectrum
  • Урок 19. 00:05:06
    A note about terminology of Fourier features
  • Урок 20. 00:10:49
    How and why it works
  • Урок 21. 00:07:22
    Inverse Fourier transform for bandstop filtering
  • Урок 22. 00:07:12
    How it works, speed tests
  • Урок 23. 00:02:11
    The fast inverse Fourier transform
  • Урок 24. 00:06:50
    The perfection of the Fourier transform
  • Урок 25. 00:07:25
    Using the fft on matrices
  • Урок 26. 00:16:21
    Sampling and frequency resolution
  • Урок 27. 00:11:14
    Time-domain zero padding
  • Урок 28. 00:07:50
    Frequency-domain zero padding
  • Урок 29. 00:09:14
    Sampling rate vs. signal length
  • Урок 30. 00:10:06
    Aliasing
  • Урок 31. 00:05:40
    Signal stationarity and non-stationarities
  • Урок 32. 00:16:00
    Effects of non-stationarities on the power spectrum
  • Урок 33. 00:13:10
    Solution to understanding nonstationary time series
  • Урок 34. 00:09:51
    Windowing and Welch's method
  • Урок 35. 00:11:34
    Instantaneous frequency
  • Урок 36. 00:11:14
    How the 2D FFT works
  • Урок 37. 00:06:07
    Rhythmicity in walking (gait)
  • Урок 38. 00:07:04
    Rhythmicity in electrical brain waves
  • Урок 39. 00:03:13
    Time series convolution
  • Урок 40. 00:08:16
    Narrowband temporal filtering
  • Урок 41. 00:07:32
    2D image filtering
  • Урок 42. 00:05:55
    Image narrowband filtering
  • Урок 43. 00:04:12
    Real data from trends.google.com!
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