thuyết trình về noise cancellation
DESCRIPTION
Noise cancellation slide presentationTRANSCRIPT
Noise cancellationNoise cancellation
Bui Le SonVo Phuc Luan
11ECE2
AssumptionAssumptionAssume that we have a input signal:
x(n) = d(n) + v1(n)
With d(n) is signal source and v1(n) is noise source.
We want to remove the noise v1(n), we use a sensor to record the noise v2(n),which is the input to the Wiener filter that is used to estimate the noise v1(n), the Wiener-Hopf equation are:
Rv2w = rv1v2
Derive W-H solutionDerive W-H solutionWe consider the same data model as for
filtering: x(n) = d(n) + v1(n) or x = d + v1
where d = [d(n), . . . , d(n − p + 1)]T
and v1 = [v1(n), . . . , v1(n − p + 1)]T .
This time we estimate v1(n) from a correlated noise source v2(n), and estimate d(n) as
dˆ(n) = x(n) − v1ˆ(n) with
v1ˆ(n) = wTv2
where v2 = [v2(n), . . . , v2(n − p + 1)]T .
To estimate v1(n) from v2(n), we start from the Wiener-Hopf equations
Rv2w = rv1v2
Since rv1v2 is generally not known, we can rewrite this as
rv1v2 = E{v1(n)v2*} = E{(d(n) + v1 (n)) v2
*} = E{x(n) v2
*} = rxv2
and thus the Wiener-Hopf equations can be written as
Rv2w = rxv2
As already mentioned, d(n) is then estimated as
dˆ(n) = x(n) − v1ˆ(n) with v1ˆ(n) = wTv2
ExampleExample
ExampleExample
ProblemProblem
MATLABMATLABDescription: This on of the project that shows
how to implement Wiener filter as noise cancellations. Our desired response is d(n) output is x(n). We have noise v(n), v1(n) and v2(n) that have the following relationship v1(n)= 0.8*v1(n-1)+v(n) and
v2(n)= -0.6v2(n-1)+v(n)
where v(n) is AWGN.
The ouptut is x(n)=d(n)+v1(n)
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ConclusionConclusionThis method is useful is in air-to-air communications between pilots in fighter aircraft or in air-to-ground communication between a pilot and a control tower. Since there is often a large amount of engine and wind noise within the cockpit of the fighter aircraft, communication is often a difficult problem. However , if a secondary microphone is placed within the cockpit of an aircraft, then one may estimate the noise that is transmitted when the pilots speaks into microphone, and subtract this estimate from the transmitted signal, thereby increasing the signal-to-noise- ratio.