Adaptive Filter Parameter Space and Validation
- To test and validate the LMS adaptive filter algorithm for noise cancelation
- To explore the parameter space for the algorithm
- To test the algorithm under simulated real world (white noise) conditions
Test, validation and exploration:
- The LMS algorithm from Active Noise Control Systems and Digital Signal Processing: A Practical Approach was coded in C using Borland C++ V3.1
- The "noise" source was a 64 sample waveform generated by using a sine wave of period 8 samples and amplitude 10 units
- The "quiet" signal was the same sample waveform delayed by 4 bins
- The noise and quiet waveforms were fed into the LMS algorithm.
- The LMS output was the "error" waveform.
- The waveform was then plotted using Excel 95.
- A graphic showing convergence vs number of filter taps was generated
- A graphic showing convergency vs XXX parameter was generated
Simulated real world test:
- White noise was generated by Cool Edit and saved as a text file
- The LMS algorithm was then applied to the white noise
- The original noise, a 16 tap solution and a 64 tap solution were graphed
For this data there seemed to be a law of diminishing returns after about 8 taps (the period of the noise source).
The u size experiment was conducted with a 8 tap filter.
The filter settings were very touchy. 128 and 256 tap settings were attempted but they did not converge. I suspect that we are getting cumulative errors in the algorithm.