ARTIFICIAL NEURAL NETWORKS FOR REAL-TIME ESTIMATION OF BASIC WAVE-FORMS OF VOLTAGES AND CURRENTS

被引：41

作者：

CICHOCKI, A ^{[1
]}

LOBOS, T ^{[1
]}

机构：

[1] WROCLAW TECH UNIV,PL-50370 WROCLAW,POLAND

来源：

IEEE TRANSACTIONS ON POWER SYSTEMS | 1994年 / 9卷 / 02期

关键词：

D O I：

10.1109/59.317683

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

New parallel algorithms for estimation of Parameters of sinewave contaminated by noise are Proposed. The problem of estimation is formulated as an optimization problem and solved by using the gradient descent method. Algorithms based on the least absolute value, the least-squares and the minimax ( Chebyshev ) criteria are developed and compared. The implementation of the algorithms by an appropriate neural network is also given. Illustrative computer simulation results confirm validity and high performance of the proposed solution.

引用

页码：612 / 618

页数：7

共 15 条

[1] NEURAL NETWORKS FOR SOLVING SYSTEMS OF LINEAR-EQUATIONS AND RELATED PROBLEMS [J].