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One of the most wide spread applications of adaptive filtering is
adaptive noise cancellation. The basic prerequisite for this realization
is the availability of the two inputs called primary and reference. The
primary signal consists of speech s(n) plus noise n1(n) while the
reference signal consists of noise n(n) alone. The two noise signals
n1(n) and n(n) are correlated and hi(n) is the impulse response of the
noise path from the noise source to the primary microphone. Assuming
that the signals are discretetime and the sampling period is T=1, the
primary input can be written as
xp(n) = s(n) +n1(n) . (1)
where speech signal s(n) and noise signal n1(n) must be uncorrelated
ADAPTIVE BLIND NOISE SUPPRESSION (ABNS) SCHEME
As mentioned in the introduction, the specific features of the noise in some speech processing applications suggest the usage of narrow-band notch filters. They have to meet the following requirements:
To adapt as fast as possible to the changes in the noise which might be quite rapid, for example car engine noise;
The cancelled portions of the spectrum should be as narrow as possible in order to prevent speech signal distortions.
Both requirements could be met much easier using IIR adaptive filters instead of FIR adaptive filters. IIR filters are usually avoided because they create a lot of stability problems. To overcome this problem we use a realization based on second order Gray-Markel lattice circuit. Using this circuit it becomes possible to implement a second order notch/bandpass section Fig. 3.The advantages of such a realization are first, it has extremely low pass band sensitivity that means resistance to quantization effects. Second, it is very convenient for realization of adaptive notch filters because it is possible tocontrol independently the notch frequency and the bandwidth
xp(n) = s(n) +n1(n) . (1)
where speech signal s(n) and noise signal n1(n) must be uncorrelated
ADAPTIVE BLIND NOISE SUPPRESSION (ABNS) SCHEME
As mentioned in the introduction, the specific features of the noise in some speech processing applications suggest the usage of narrow-band notch filters. They have to meet the following requirements:
To adapt as fast as possible to the changes in the noise which might be quite rapid, for example car engine noise;
The cancelled portions of the spectrum should be as narrow as possible in order to prevent speech signal distortions.
Both requirements could be met much easier using IIR adaptive filters instead of FIR adaptive filters. IIR filters are usually avoided because they create a lot of stability problems. To overcome this problem we use a realization based on second order Gray-Markel lattice circuit. Using this circuit it becomes possible to implement a second order notch/bandpass section Fig. 3.The advantages of such a realization are first, it has extremely low pass band sensitivity that means resistance to quantization effects. Second, it is very convenient for realization of adaptive notch filters because it is possible tocontrol independently the notch frequency and the bandwidth
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