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MSHKUZ001 Final Year Thesis, Electrical Engineering, University of Cape Town

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EEE4022S-Active-Noise-Control

MSHKUZ001 Final Year Thesis, Electrical Engineering, University of Cape Town

Maintained by Kuziwakwashe Stephen Mashingaidze

1.) ACTIVE NOISE CONTROL USING ARDUINO DUE

i.) MONO CHANNEL IMPLEMENTATION

  • Adaptive filter based upon least mean squares algorithm implementation
  • 'N' denotes filter tap count
  • 'mu' denotes LMS step-size
  • Upload to Arduino Due
  • Reference microphone signal to be connected to pin A0 (after 1.56V biasing)
  • Error microphone signal to be connected to pin A1 (after 1.56V biasing)
  • Output available at DAC0 (biased by 1.56V)

ii.) DUAL CHANNEL IMPLEMENTATION

  • Adaptive filter based upon least mean squares algorithm implementation
  • 'N' denotes filter tap count
  • 'mu' denotes LMS step-size
  • Upload to Arduino Due
  • Left channel reference microphone signal to be connected to pin A0 (after 1.56V biasing)
  • Right channel reference microphone signal to be connected to pin A2 (after 1.56V biasing)
  • Left channel error microphone signal to be connected to pin A1 (after 1.56V biasing)
  • Right channel error microphone signal to be connected to pin A3 (after 1.56V biasing)
  • Left channel output available at DAC0 (biased by 1.56V)
  • Right channel output available at DAC1 (biased by 1.56V)

2.) MATLAB SIMULATIONS

  • Connect microphone to PC, then run code

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MSHKUZ001 Final Year Thesis, Electrical Engineering, University of Cape Town

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