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利用ＢＰ神经网络动态系统对一类非线性时变系统的状态进行了估计。利用神经网络的“学习－遗忘”特性，提出了非线性时变系统的自适应状态观测器，对其结构及特性进行了讨论。仿真结果表明这种自适应状态观测器能跟踪系统参数及状态的变化。
The state of a class of nonlinear time-varying system is estimated by using BP neural network dynamic system. Using the learning-forgetting characteristic of neural network, an adaptive state observer for nonlinear time-varying systems is proposed and its structure and characteristics are discussed. Simulation results show that the adaptive state observer can track the system parameters and state changes.