标题： 一种零吸引四元数值最小均方算法用于稀疏系统识别 显示英文标题

标题： A Zero-attracting Quaternion-valued Least Mean Square Algorithm for Sparse System Identification

摘要： 最近，四元数值信号处理受到了越来越多的关注。 在本文中，首次研究了四元数值稀疏系统辨识问题，并通过考虑四元数值自适应权向量的$l_1$范数推导出了一种零吸引四元数值最小均方（LMS）算法。 通过将系统的稀疏性信息融入更新过程，实现了更快的收敛速度，这由仿真结果验证。 显示英文摘要

摘要： Recently, quaternion-valued signal processing has received more and more attention. In this paper, the quaternion-valued sparse system identification problem is studied for the first time and a zero-attracting quaternion-valued least mean square (LMS) algorithm is derived by considering the $l_1$ norm of the quaternion-valued adaptive weight vector. By incorporating the sparsity information of the system into the update process, a faster convergence speed is achieved, as verified by simulation results.