对于线性非时变的无源二端口网络，在零初始条件下，若存在互易性及对称性，则其电路参数具有一定的特殊性。
If reciprocity and symmetry exist for passive two port networks of linear time invariant under zero intial condition, the circuit parameters will have some important characters.
本文针对船舶操纵这种非线性、时变参数控制对象，提出了一种采用神经网络自适应PID控制方案。
In this paper, according to nonlinear and time-varying parameter of ship maneuvering, the scheme of neural network adaptive PID control is proposed.
对于非线性，大时延、变参数的造纸过程灰份含量的控制，本文给出了一种神经网络控制方法。
In this paper, a neural network controller is designed for ash content control of papermaking process, neural networks are trained by using the output error of the controlled plant directly.
基于人工神经网络的非线性映射特性，在三维有限元计算的基础上，结合大坝原型观测资料，提出了大坝参数时变规律的反演方法。
On the basis of the nonlinear characteristics of ANN and 3-D FEM computation, an inversion method for the time-varying regularity of dam parameters is presented with the observation data used.
基于人工神经网络的非线性映射特性，在三维有限元计算的基础上，结合大坝原型观测资料，提出了大坝参数时变规律的反演方法。
On the basis of the nonlinear characteristics of ANN and 3-D FEM computation, an inversion method for the time-varying regularity of dam parameters is presented with the observation data used.
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