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3.4.3 Notch and comb filters

Explore the effectiveness of notch and comb filters in removing periodic artifacts. Learn about Wiener and adaptive filters for interference removal and synchronization techniques. Understand optimal filter selection for stationary and non-stationary signals, noise characteristics, and real-time processing. Discover adaptive filtering with available reference.

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3.4.3 Notch and comb filters

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  1. 3.4.3 Notch and comb filters To remove periodic artifacts (periodic in the time domain) (discrete in the frequency domain)

  2. 3.4.3 Notch and comb filters To remove periodic artifacts (periodic in the time domain) (discrete in the frequency domain) Figure 3.40

  3. DC gain = ?

  4. Figure 3.41

  5. Figure 3.42

  6. Figure 3.43

  7. Figure 3.44

  8. Figure 3.45

  9. 3.5 Optimal filtering: the Wiener filter

  10. 3.6 Adaptive filters for removal of interference

  11. 3.7 filter selection • Synchronized averaging: • Signal: stationary or cyclo-stationary • Signal: Periodic or quasi-periodic • Synchronization is possible • Noise: stationary, random, uncorrelated with the signal, zero mean

  12. MA averaging: • Signal: stationary (over the window duration) • Noise: stationary (over the window duration) , zero mean • Signal: low-frequency • on-line, real-time

  13. Frequency-domain fixed filter: • Signal: stationary • Noise: stationary • signal is band-limited or noise is band-limited

  14. Optimal filter: * Signal: stationary

  15. Adaptive filter: • Signal: not necessarily stationary • uncorelated between signal and noise • No information about the signal and the noise • Reference is available

  16. Adaptive filter:

  17. HW

  18. 5. N=2 - 8 Fc = 0.5 – 5

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