摘要
在模拟电路模糊组识别过程中,模糊C均值聚类(FCM,fuzzy C-means clustering algorithm)易陷入局部最优。针对此种缺陷,提出一种基于ICQPSO的FCM模拟电路可诊断元件集识别方法。首先对ICQPSO算法进行了分析;然后介绍了FCM算法及其有效性指标,在此基础上研究了基于ICQPSO的FCM方法;最后以某模拟电路为例进行了仿真实验。仿真结果表明,将该方法应用于模拟电路可诊断元件集的识别是行之有效的。
Fuzzy C-means clustering algorithm(FCM) is easy to fall into local optimum in the process of fuzzy group identification of analog circuits. An identification algorithm for the testable elements set of FCM analog circuits based on ICQPSO is proposed. The ICQPSO algorithm is analyzed firstly, and then the FCM algorithm and its validity index are introduced. On this basis, the FCM algorithm based on ICQPSO is investigated. Final- ly, one analog circuit is taken as an simulation example. The simulation result shows that this method can be ef- fectively applied to the identification of testable element set of analog circuits.
作者
刘新海
马彦恒
杨森
LIU Xin-hai;MA Yan-heng;YANG Sen(Department of Unmanned Aerial System Engineering, Ordanee Engineering College, Shijiazhuang 050003, Chin)
出处
《测控技术》
CSCD
2017年第11期40-44,共5页
Measurement & Control Technology