摘要
基于人工鱼群算法收敛速度较快、具有良好的全局寻优能力等优点,本文将人工鱼群算法运用到信号的盲源分离中,提出一种基于改进人工鱼群的信号盲源分离方法。该方法以峭度的绝对值之和作为目标函数,采用独立分量分析的方法,采用改进的人工鱼群算法寻找目标函数最大值,进而确定最优分离矩阵,对信号进行分离。仿真结果表明,该方法相比原方法,在分离性能、算法收敛性和运算速度方面均具有明显优势。
Based on the advantages of the artificial fish swarm algorithm,such as fast convergence and good global optimization ability,the artificial fish swarm algorithm is applied to the blind source separation of signals,and a signal blind source separation method based on the improved artificial fish swarm algorithm is proposed.In this method,the sum of the absolute value of kurtosis is taken as the objective function,and the improved artificial fish swarm algorithm is used to find the maximum value of the objective function.Simulation results show that the proposed method has obvious advantages over the basic artificial fish swarm algorithm in terms of separation performance,algorithm convergence and operation speed.
作者
方宇
余晨钟
FANG Yu;YU Chenzhong(College of Urban and Rail Transit,Shanghai University of Engineering Science,Shanghai 201620,China)
出处
《智能计算机与应用》
2020年第8期105-109,共5页
Intelligent Computer and Applications
关键词
人工鱼群算法
独立成分分析
盲源分离
artificial fish swarm algorithm
rolling bearing
blind source separation
