1 / 13

Sampling

Sampling. COS 323. Signal Processing. Sampling a continuous function. . Signal Processing. Convolve with reconstruction filter to re-create signal. . =. How to Sample?. Reconstructed signal might be very different from original: “aliasing”. . . Why Does Aliasing Happen?.

malina
Download Presentation

Sampling

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Sampling COS 323

  2. Signal Processing • Sampling a continuous function 

  3. Signal Processing • Convolve with reconstruction filter tore-create signal  =

  4. How to Sample? • Reconstructed signal might be very different from original: “aliasing”  

  5. Why Does Aliasing Happen? • Sampling = multiplication by shah function III(x) (also known as impulse train)  = III(x)

  6. Fourier Analysis • Multiplication in primal space = convolution in frequency space • Fourier transform of III is III sampling frequency F(III(x)) III(x)

  7. Fourier Analysis • Result: high frequencies can “alias”into low frequencies  =

  8. Fourier Analysis • Convolution with reconstruction filter = multiplication in frequency space  =

  9. Aliasing in Frequency Space • Conclusions: • High frequencies can alias into low frequencies • Can’t be cured by a different reconstruction filter • Nyquist limit: can capture all frequencies iff signal has maximum frequency  ½ sampling rate = 

  10. Filters for Sampling • Solution: insert filter before sampling • “Sampling” or “bandlimiting” or “antialiasing” filter • Low-pass filter • Eliminate frequency content above Nyquist limit • Result: aliasing replaced by blur OriginalSignal Prefilter Sample ReconstructionFilter ReconstructedSignal

  11. Ideal Sampling Filter • “Brick wall” filter:box in frequency • In space: sinc function • sinc(x) = sin(x) / x • Infinite support • Possibility of “ringing”

  12. Cheap Sampling Filter • Box in space • Cheap to evaluate • Finite support • In frequency: sinc • Imperfect bandlimiting

  13. Gaussian Sampling Filter • Fourier transform of Gaussian = Gaussian • Good compromise as sampling filter: • Well approximated by function w. finite support • Good bandlimiting performance

More Related