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The purpose of adaptive noise cancellation is to improve the signal-to-noise ratio (SNR) of a signal by removing noise from the signal that you receive. A typical example of this application is the communication between a pilot, who is inside a jet aircraft, and a ground control tower. A jet engine can produce noise of over 140 dB, but normal human speech is below 50 dB. If you are in the ground control tower, you might have difficulty hearing the pilot's speech clearly. In this situation, you can use adaptive filters to remove the jet engine noise while retaining the pilot's speech.
The following figure shows a diagram of the jet engine noise cancellation system.
In the previous figure, s(n) is the pilot's speech that you need to acquire. However, you cannot acquire s(n) directly. You only can acquire s(n) + v1(n), where v1(n) is the jet engine noise. You cannot acquire v1(n) directly either. To remove v1(n) from s(n) + v1(n), you can use an adaptive filter.
You first must use a sensor to acquire only the jet engine noise v2(n) and send this signal into the adaptive filter. If you compare the previous figure with the diagram of the adaptive filter, the signal s(n) + v1(n) in the previous figure corresponds to d(n) in the diagram of the adaptive filter. v2(n) corresponds to x(n).
In the previous figure, if s(n) is uncorrelated with the jet engine noise v(n), and if both v1(n) and v2(n) are highly correlated with v(n), the noise cancellation system can estimate the jet engine noise v1(n) by adjusting the coefficients of the adaptive filter iteratively. When the output signal y(n) becomes close to v1(n), the system then can remove the engine noise. In the previous figure, e(n) denotes the resulting signal that is close to s(n).
Refer to the Adaptive Noise Cancellation.lvproj file in the examples\Adaptive Filters\Applications\Adaptive Noise Cancellation directory for an example that uses the LabVIEW Adaptive Filter Toolkit to remove background noise.