An Acoustic Echo Cancellation Technique Based on Kurtosis Subgradient Projection Algorithm
Jie Qiao, Li Zhao, Zou Cai-rong
Abstract
Jie Qiao, Li Zhao, Zou Cai-rong
Abstract
Based on the technique of projection onto convex sets (POCS), a kurtosis subgradient projection (KSP) algorithm is proposed in this paper which is applied in the scheme of the acoustic echo cancellation successfully. KSP algorithm utilizes the kurtosis of error signal after adaptive filtering as the projection area and expands this projection area to half space by using the definition of subgradient. Finally a simply projection expression can be got by projecting onto this half space. Experiments indicate that not only the convergence speed is increased but also the robustness to noise is enhanced compared to traditional method. Additionally, system performance gets promoted evaluated either by mean square error (MSE) or by echo path misalignment.
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Based on the technique of projection onto convex sets (POCS), a kurtosis subgradient projection (KSP) algorithm is proposed in this paper which is applied in the scheme of the acoustic echo cancellation successfully. KSP algorithm utilizes the kurtosis of error signal after adaptive filtering as the projection area and expands this projection area to half space by using the definition of subgradient. Finally a simply projection expression can be got by projecting onto this half space. Experiments indicate that not only the convergence speed is increased but also the robustness to noise is enhanced compared to traditional method. Additionally, system performance gets promoted evaluated either by mean square error (MSE) or by echo path misalignment.
Key concepts: Subgradient method, Kurtosis, Robustness (evolution), Projection (relational algebra), Algorithm, Echo (communications protocol), Computer science, Convergence (economics)