文献类型：会议论文

英文题名：A harmonics analysis method based on triangular neural network

作者：Xiao Xiuchun[1,2,3];Jiang Xiaohua[3];Lu Xiaomin[3];Chen Botao[1]

机构：[1]Guangdong Ocean Univ, Coll Informat, Zhanjiang 524025, Peoples R China;[2]Zhejiang Univ, State Key Lab CAD&CG, Hangzhou 310058, Zhejiang, Peoples R China;[3]Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510275, Guangdong, Peoples R China

会议论文集：IITA International Conference on Control, Automation and Systems Engineering

会议日期：JUL 11-12, 2009

会议地点：Zhangjiajie, PEOPLES R CHINA

语种：英文

外文关键词：Harmonics analysis; power system; triangular functions; neural network

外文摘要：Aiming at fast and effectively evaluating harmonics in the power system, a triangular neural network is constructed, of which the hidden neurons are activated with triangular functions. Based on gradient descent method, the learning rules (i.e., weights-iterative-formula) for the constructed neural network are derived. Then global-convergence of the weights-iterative-formula is proved. As the results, a weights-direct-determination method is achieved, which could obtain the optimal weights of such a neural network in one step by using pseudo-inverse. Furthermore, several numerical tests have been conducted to apply this method to some harmonics models. The simulation results substantiate this method can be used to fast and precisely evaluate the harmonic components.