Nonlinear acoustic echo cancellation based on pipelined Hermite filters
关键字：ADAPTIVE PREDICTION; IDENTIFICATION; ALGORITHM; ADAPTATION
摘要：This paper introduces a new class of nonlinear filters for nonlinear acoustic echo cancellation (NLAEC) based on Hermite nonlinear filters (HNFs), which is a sub-class of linear -in -the -parameters nonlinear filters (LIPNFs). Specifically, the basis functions of HNFs include cross -terms of the expanded inputs at different time instants, and are mutually orthogonal for white normally distributed input signals. Although HNFs yield good performance for NLAEC, they suffer from high computational complexity. To tackle this problem, a computationally efficient pipelined iant of HNFs is introduced. The pipelined HNFs (PHNFs) include a nonlinear part followed by a linear one such that the input space is first expanded nonlinearly and then cast by a linear mapping to the output space. Experimental results using both synthesized and real data, and involving several nonlinear scenarios show the effectiveness of the proposed approach.
卷号：220
期号：-
是否译文：否
