Memory Proportionate APA with Individual Activation Factors for Acoustic Echo Cancellation
Memory Proportionate APA with Individual Activation Factors for Acoustic Echo Cancellation
复制标题
DOI：
10.1109/taslp.2014.2318519
复制
发表时间：
2014-06
期刊：
影响因子：
--
通讯作者：
Haiquan Zhao;Yi Yu;Shibin Gao;Xiangping Zeng;Zhengyou He
中科院分区：
文献类型：
--
作者：
Haiquan Zhao;Yi Yu;Shibin Gao;Xiangping Zeng;Zhengyou He
针对声回波抵消（AEC）场景下的稀疏系统识别问题，提出了一种个体激活因子记忆比例仿射投影算法（IAF-MPAPA）。通过对每个自适应滤波系数使用单个激活因子，而不是像标准比例仿射投影算法（PAPA）那样使用全局激活因子，所提出的IAF-MPAPA在系数上的自适应能量得到更好的分布，从而提高了收敛性能。此外，得益于比例系数的记忆特性，其计算复杂度低于PAPA和改进的PAPA （IPAPA）。在高度稀疏脉冲响应的AEC和立体AEC （SAEC）环境下，仿真结果表明，IAF-MPAPA在未知脉冲响应突然变化时的收敛速度和跟踪能力优于PAPA、IPAPA和记忆IPAPA （MIPAPA）。
An individual-activation-factor memory proportionate affine projection algorithm (IAF-MPAPA) is proposed for sparse system identification in acoustic echo cancellation (AEC) scenarios. By utilizing an individual activation factor for each adaptive filter coefficient instead of a global activation factor, as in the standard proportionate affine projection algorithm (PAPA), the adaptation energy over the coefficients of the proposed IAF-MPAPA can achieve a better distribution, which leads to an improvement of the convergence performance. Moreover, benefiting from the memory characteristics of the proportionate coefficients, its computational complexity is less than the PAPA and improved PAPA (IPAPA). In the context of AEC and stereophonic AEC (SAEC) for highly sparse impulse responses, simulation results indicate that the proposed IAF-MPAPA outperforms the PAPA, IPAPA, and memory IPAPA (MIPAPA) in terms of the convergence rate and tracking capability when the unknown impulse response suddenly changes.