Convex Combination Noise Reduction Method Based on the Minimum Difference Between Error Square and Error Square Logarithm

Abstract

The invention discloses a convex combination noise reduction method based on the minimum difference between the error square and the error square logarithm. The steps mainly include: A. reference signal collection, collecting the output signal of the sound sensor near the noise source, and obtaining the reference signal Discrete value x(n), the input signal vector of its filter is X(n)=[x(n),x(n‑1),...,x(n‑L+1)] T ; B, convex combination, the output signal y of the large-step filter 1 (n) and small step size filter output signal y 2 (n) Convex combination by weight λ(n) to obtain combined filter output signal y(n), y(n)=λ(n)y 1 (n)+(1‑λ(n))y 2 (n); C, residual error signal, collect the output signal of the sound sensor near the loudspeaker, obtain the sound signal d(n) after canceling the noise, and draw residual error signal e(n); D, combined filter tap weight Vector update; E, filter weight update; F, filter weight limit; G, repeat, let n=n+1, repeat the steps of A to F. Its convergence speed is fast, the steady-state error is small, and the noise reduction performance is good.

Description

technical field [0001] The invention belongs to the technical field of adaptive control of noise. Background technique [0002] With the improvement of people's living standards, people pay more and more attention to noise pollution, especially some special working environments are exposed to severe noise for a long time, and the health of people working there will be seriously affected; Affect the performance of the equipment and shorten the service life of the equipment. In order to eliminate and reduce these hazards and pollution, effective noise control (noise reduction) measures must be taken to control the increasingly serious noise. [0003] Active noise control (noise reduction) technology is a new technology developed in the field of noise control in recent decades. With the development of electronic technology, the application of adaptive filter technology to active noise control has become the focus of active noise control research. This noise reduction method ...

AI Technical Summary

Problems solved by technology

Its filter weight update is linearly positively correlated with the residual error e(n), so that the filter weight update value is more sensitive to the error, making the convergence speed faster and the steady-state error smaller, but its convergence speed and steady-state error are still relatively small. to be further improved

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