Exponential Function Echo Cancellation Method Based on One-Norm Zero Attraction

Abstract

An exponential function echo cancellation method based on one-norm zero attraction. The invention discloses a zero-norm sub-band echo cancellation method, the steps of which include: A, remote signal sampling; B, echo signal estimation; C, echo signal cancellation; D, filter tap weight coefficient update; n=n+1, repeat steps B, C, and D to realize real-time echo cancellation; it uses a norm of the weight coefficient vector in the derivation of the weight coefficient vector update formula, namely γ||W(n)| | 1 , where γ is the proportional parameter of the one-norm of the weight coefficient vector, and the zero attractor ρ(n) is obtained in the derivation, ρ(n)=b·sgnW(n), that is, the weight coefficient vector goes to zero for the sparse system The update speed is faster; when the weight is updated, the exponential function is used as the cost function method, so that the cost function becomes And a new step size factor is introduced, so that in the case of Gaussian signals and sparse systems, the output signal of the filter can obtain faster convergence and lower steady-state misalignment.

Description

technical field [0001] The invention relates to an exponential function echo cancellation method based on a norm zero attraction. Background technique [0002] As an important branch of information technology, adaptive signal processing has been widely used in the field of communication. In the field of communication, echo cancellation is a hot spot that attracts much attention and challenges. The sound will form an echo after multiple reflections in a closed space, and the echo will also be formed in the signal transmission due to the impedance mismatch in the transmission medium. The communication echo can be eliminated by the system identification model: the identified system is the echo channel, and the output of the system identification is the estimate of the echo signal, and the echo can be eliminated by subtracting the voice signal containing the echo signal from the estimate of the echo signal, which is The principle of adaptive echo canceller. [0003] Least mea...

AI Technical Summary

Problems solved by technology

For the characteristics of the sparse system, although the LMS algorithm adds a norm to form a zero attractor to speed up the convergence speed of the original algorithm, the linear combination in the LMS algorithm is still used in the update formula of the filter weight coefficient vector In this way, the weight coefficient vector of the filter maintains a fixed speed in the update, so the sensitivity to useful signals at different times decreases. Therefore, the convergence speed of the original algorithm still needs to be improved.

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