Noise Cancellation Example :: Adaptive Filters and Adaptive Training (Neural Network Toolbox)

Neural Network Toolbox

Noise Cancellation Example

Consider a pilot in an airplane. When the pilot speaks into a microphone, the engine noise in the cockpit is added to the voice signal, and the resultant signal heard by passengers would be of low quality. We would like to obtain a signal that contains the pilot's voice, but not the engine noise. We can do this with an adaptive filter if we obtain a sample of the engine noise and apply it as the input to the adaptive filter.

Here we adaptively train the neural linear network to predict the combined pilot/engine signal m from an engine signal n. Notice that the engine signal n does not tell the adaptive network anything about the pilot's voice signal contained in m. However, the engine signal n. does give the network information it can use to predict the engine's contribution to the pilot/engine signal m.

The network will do its best to adaptively output m. In this case, the network can only predict the engine interference noise in the pilot/engine signal m. The network error e is equal to m, the pilot/engine signal, minus the predicted contaminating engine noise signal. Thus, e contains only the pilot's voice! Our linear adaptive network adaptively learns to cancel the engine noise.

Note, in closing, that such adaptive noise canceling generally does a better job than a classical filter because the noise here is subtracted from rather than filtered out of the signal m.

Try demolin8 for an example of adaptive noise cancellation.

Prediction Example Multiple Neuron Adaptive Filters