基于遗传算法过程信号的盲分离

Blind Signal Sepration Based on Genetic Algorithm for Process Signal

盲分离神经网络算法存在着容易陷入局部极小点、收敛速度慢的缺点 .提出采用遗传算法优化盲分离神经网络权值的初值 ,将遗传算法与 HJNN结合形成 GA- HJNN算法 ,可迅速得到最佳盲分离神经网络的权值矩阵 ,实现对过程信号的去噪 .通过实验对 2种算法进行了比较 .

One of the main weak points of the blind separation algorithm of HJNN is that the optimal procedure is easily stacked into the local minimal value and it causes slow convergence. Based on genetic algorithm (GA), this paper proposed GA HJNN algorithm to optimize the initial value of the weight of HJNN so as to obtain the optimum weight matrix quickly and realize the denoising of the process signal. The comparison between the two algotithms was given with experiment.