Adaptive step size techniques for decorrelation and blind source separation
Adaptive step size techniques for decorrelation and blind source separation
复制标题
DOI：
10.1109/acssc.1998.751515
复制
发表时间：
1998-11
期刊：
影响因子：
--
通讯作者：
Scott C. Douglas;Andrzej Cichocki
中科院分区：
文献类型：
--
作者：
Scott C. Douglas;Andrzej Cichocki
对于去相关和源分离任务，从基于梯度的自适应算法中获得良好性能通常需要仔细选择步长参数。在本文中，我们概述了这些系统步长参数的在线计算方法。特别强调了一类用于去相关和盲源分离的自然梯度算法的梯度自适应步长。文中还提供了验证其有效行为的模拟。
Careful selection of step size parameters is often necessary to obtain good performance from gradient-based adaptive algorithms for decorrelation and source separation tasks. In this paper, we provide an overview of methods for the on-line calculation of step size parameters for these systems. A particular emphasis is placed on gradient adaptive step sizes for a class of natural gradient algorithms for decorrelation and blind source separation. Simulations verifying their useful behaviors are provided.