【摘要】 介绍一种提高收敛速度的基于自适应在线学习的盲信号分离算法,以Kullback-Leibler散度作为代价函数,运用随机梯度下降导出算法,在估计分离矩阵的同时更新学习率。实验证明,该算法对于混合图像信号能够有效地分离,利用自适应学习参数提高了盲信号分离的收敛速度及算法性能,结果证实了算法的有效性。更多还原

【Abstract】 A novel online learning algorithm with selfadaptive learning rates for blind separation of signals is presented to improve the convergence rate. The KullbackLeibler divergence is used as cost function,and the standard stochastic gradient descent method adopted. The learning rate is adjusted during the learning process according to a set of differential equations. Computer simulation results show that the independent sources can be extracted from the hybrid mixture of image signals by using the presented algorithm.更多还原