By Jacob Benesty, Constantin Paleologu, Tomas Gänsler, Silviu Ciochină
Single-channel hands-free teleconferencing platforms have gotten renowned. for you to increase the conversation caliber of those structures, increasingly more stereophonic sound units with loudspeakers and microphones are deployed. a result of coupling among loudspeakers and microphones, there is powerful echoes, which make real-time verbal exchange very tough. the way we all know to cancel those echoes is through a stereo acoustic echo canceller (SAEC), that are modelled as a two-input/two-output approach with actual random variables. during this paintings, the authors recast this challenge right into a single-input/single-output procedure with complicated random variables because of the generally linear version. From this new handy formula, they re-derive an important features of a SAEC, together with id of the echo paths with adaptive filters, double-talk detection, and suppression.
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Extra resources for A Perspective on Stereophonic Acoustic Echo Cancellation
On the other hand, when the algorithm starts to converge, σe (n) ≈ σv and μVSS (n) ≈ 0. This is exactly what we desire to have both good convergence and low misadjustment. So in principle, the excess MSE and misadjustment of the VSS-NLMS should be Jex (∞) ≈ 0, M ≈ 0. 83) is the estimation of the variance of the error signal, and λw = 1 − 2C1w L is an exponential window with Cw ≥ 3. As we can notice, this approach was derived with almost no assumptions as compared to all other algorithms belonging to the same family.
33–61, 1998. 22. J. Benesty and S. L. Gay, “An improved PNLMS algorithm,” in Proc. IEEE ICASSP, 2002, pp. 1881–1884. 23. C. Paleologu, J. Benesty, and S. Ciochin˘ a, “A variable step-size proportionate NLMS algorithm for echo cancellation,” Revue Roumaine des Sciences Techniques – Serie Electrotechnique et Energetique, vol. 53, no. 3, pp. 309–317, 2008. 24. J. Benesty, F. Amand, A. Gilloire, and Y. Grenier, “Adaptive ﬁltering algorithms for stereophonic acoustic echo cancellation,” in Proc. IEEE ICASSP, 1995, pp.
Benesty, “Investigation of several types of nonlinearities for use in stereo acoustic echo cancellation,” IEEE Trans. , vol. 9, pp. 686–696, Sept. 2001. 10. B. D. Rao and B. Song, “Adaptive ﬁltering algorithms for promoting sparsity,” in Proc. IEEE ICASSP, 2003, pp. VI-361–VI-364. 11. M. S. Asif and J. Romberg, “Dynamic updating for 1 minimization,” IEEE J. Sel. , vol. 4, pp. 421–434, Apr. 2010. Chapter 4 A Class of Stochastic Adaptive Filters In this chapter, we derive, study, and analyze a class of stochastic adaptive ﬁlters for SAEC with the WL model.