MATLAB code for active noise control
2015-07-21
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Background active noise control is a method to reduce unwanted noise. ANC is achieved by introducing a cancel "noise" wave through the secondary source. These secondary sources are interconnected electronic systems that use specific signal processing algorithms to specifically cancel plans. Essentially, this involves the use of microphones and electronic circuits to produce a "noisy" sound wave that reaches the relative polarity of the microphone. This is the result of destructive interference, which cancels out the noise. The basic concept is that when two sine waves are superimposed, the generated waveform depends on the amplitude of the frequency and the relative phase of the two waves. If the original wave and the original wave are at an opposite inverse junction at the same time, the total cancellation occurs. The challenge is to determine the original signal and the direction of all interactions in the noise stack. The key technology of basic LMS algorithm failed in the implementation of ANC framework. This is due to the assumption that the filter's output (n) is made in the wrong microphone, which is not in practice. The existence of a / D / a converter and an anti aliasing filter results in a significant change in the signal caused by the wrong microphone from the output path to the received signal. This requires the effect of the quadratic path function to be incorporated into the algorithm. One solution is to place the same filter weight update path of LMS algorithm in the reference signal to realize the so-called LMS algorithm (FXLMS). FXLMS algorithm has been observed to be the most effective of all other solutions. Also, the algorithm seems to be very tolerant of errors made in the estimation, thus allowing off-line estimation of the most appropriate choice. In addition, the use of FIR filters designed for Watt makes the system very stable. But the disadvantage is that using high-order filter will make the algorithm run slowly, and the convergence speed of the algorithm depends on the accuracy of the estimation;
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噪声控制
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