Improved Online ICA Method in Natural Image
Hou Rui-ling · Beijing Youdian Xueyuan xuebao · 2010
In the conventional gradient algorithm,the convergence points are difficult to be found,an intensive analysis on the gradient adaptive online independent component (ICA) methods is presented. It indicates that the digital image is a magnitude bounded signal,the convergence point in the conventional gradient algorithm will be imposed on the learning process,making the gradient descent processing convert rise processing. It ensures that when the ending codes get to the receiver,the separation matrix can be storage at the optimal point of separation. Simulation shows that this new method is with stable performance and numerical stability,and is an efficient independent component analysis algorithm.