它通过构造伪输出辨识被控对象参数，引进反馈误差，实现对解耦神经网络的在线训练。
It can identify the parameters of a controlled object by forming a fake output and bring in a feedback error for performing an on-line training to decouple the neural network.
针对输入和输出均为时变函数或过程的实际系统建模和仿真问题，提出一种输入和输出均为时变函数的反馈过程神经网络模型。
In order to model and simulate systems with time-varying functions or processes, a feedback process neural network model with time-varying input and output functions is proposed.
利用人工神经网络，讨论了线性定常控制系统关于状态反馈、输出反馈及动态补偿器的极点配置问题。
By Using an artificial neural network, the pole assignment problem of state feedback, output feedback and dynamic output feedback compensators in linear control system are discussed.
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