A method for ica for complex - valued sources 一种针对复值信号的独立分量分析方法
A novel algorithm is proposed for training complex - valued neural networks 摘要提出了一种新型复数前馈神经网络的学习算法。
Based on the second order statistics , an algorithm is proposed to separate mixed complex - value signals online 摘要基于二阶统计量,对在线分离复值混合信号法进行了研究。
The full - rank matrix is employed to find the complex - valued weights between hidden and output layers by the least mean square algorithm 利用这个满秩矩阵,通过最小平方算法就可以求得隐层和输出层之间的复数权值。
To improve learning speed , a novel method for properly initializing the parameters ( weights ) of training complex - valued neural networks is proposed 摘要为了改善学习速率,提出了一种确定复数神经网络初始权值的新颖方法。