SOLVING SIMULTANEOUS LINEAR-EQUATIONS USING RECURRENT NEURAL NETWORKS

被引:15
|
作者
WANG, J [1 ]
LI, H [1 ]
机构
[1] TEXAS TECH UNIV,DEPT COMP SCI,LUBBOCK,TX 79409
关键词
D O I
10.1016/0020-0255(94)90012-4
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Simultaneous linear algebraic equations can be found in many mathematical model formulations. In monitoring and control of dynamic systems, there is often a need for solving simultaneous linear algebraic equations in real time. In this paper, recurrent neural networks for solving simultaneous linear algebraic equations are proposed. The asymptotic stability of the proposed neural networks and solvability of simultaneous linear equations by using the neural networks are substantiated. A circuit schematic for realizing the neural networks is described. The results of numerical simulations are discussed via illustrative examples. An extension of the recurrent neural networks for solving quadratic programming problems subject to equality constraints is also discussed.
引用
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页码:255 / 277
页数:23
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