Simulation results show that the fuzzy control and neural network can take advantage of each other to possess a good performance in the uncertain nonlinear system.
仿真结果表明，该方案可以实现模糊控制和神经网络的优势互补，对不确定非线性系统具有很好的控制效果。
This paper proposes a new type position controller with neural network structure, gives it 's learning rule, and do the simulation experiment on position servo system of NC machine.
本文提出了一种新型的神经网络结构的位置控制器，给出了该控制器的学习算法，并进行了数控机床位置伺服系统的仿真实验。
Aiming at problematic complexity of the nonlinear dynamic mathematical modeling of generator in the hydro-electric simulation system, a neural network based on information fusion is brought forward.
文章针对水电仿真系统中水轮发电机机组的非线性动态数学模型建模复杂问题，提出了一种基于信息融合思想的神经网络模型。
In the existing fire alarm system, create a BP neural network simulation model which is based on Wuhan Zhongshan Road Tunnel project, access to actual operation data as the training sample data,.
在现有的火灾报警系统上，以武汉中山路隧道项目为支撑，获取实际运行中的数据作为训练样本数据，建立一个BP神经网络模拟模型。
Based on this system, a dynamic neural network is used to track the change of quality characteristics during manufacturing process. Numerical simulation and practical experiment show good results.
根据提出的系统模型利用动态神经网络对加工过程质量特征参数的变化进行了跟踪实验，效果良好。
Simulation results show that extensive mapping ability of neural network and rapid global convergence of ant system can be obtained by combining ant system and neural network.
仿真实验表明：用蚁群算法训练神经网络，可兼有神经网络广泛映射能力和蚁群算法快速全局收敛的性能。
Simulation res ults prove that this new multi-step prediction based on PID-like neural network control system can effectively attenuate random noise interference and is more robust and adaptive.
仿真实验表明，基于多步预测的PID型神经网络控制系统能有效抑制随机干扰，具有较强的适应性和鲁棒性。
Thus obtains the use neural network method in the simulation the modeling is one effective method, is specially better regarding the non-linear complex system effect.
从而得出利用神经网络方法在仿真中建模是一种行之有效的方法，特别是对于非线性复杂系统效果更佳。
Finally, an adaptive noise cancelling system is designed as an example and the computer simulation results show the superior performance of the adaptive neural network filters.
最后以自适应噪声对消系统为例，进行了计算机仿真，结果显示了这种滤波器的良好性能。
Simulation results show that the designed system is of fast response, non-overshoot and it is more effective than the conventional adaptive control of machining process based on neural network.
仿真结果表明，该系统响应快，无超调，比传统的加工过程神经网络自适应控制具有更好的控制效果。
Simulation results show that this fuzzy-neural network estimator can precisely measure the value of resistance and improve the low-speed performances of DTC system efficiently.
仿真结果表明了模糊神经网络观测器可实现对定子电阻的精确检测，从而提高直接转矩控制系统的低速性能。
The simulation results are presented to demonstrate that the model of an unknown nonlinear dynamical system is built with the multilayered feedforward neural network model.
仿真实例进一步表明，采用神经网络建立未知非线性动态系统的在线模型具有可行性。
The application of RBF neural network in hardy nonlinear system and the result of simulation is introduced. An example of pH control in hydroxylamine reactor is described.
以某厂羟胺反应器的氢离子浓度控制为例，介绍了径向基函数（RBF）神经网络在强非线性对象预测控制中的应用及仿真研究结果。
A simulation program for back-propagation neural network implemented with Cprogramming language under Windows system is presented.
本文介绍一个在窗口系统下用C语言实现的后向传播神经网络(BP网络)模拟软件。
Then simulation of servo system based on both traditional control theories and neural network method is carried out separately and result of comparison is given.
通过计算机仿真，文中还给出了基于传统控制理论的伺服跟踪系统和用神经网络构建的伺服跟踪系统的仿真结果。
Then simulation of servo system based on both traditional control theories and neural network methoe is carried out separarely and result of comparison is given.
通过计算机仿真，文中还给出 了基于传统控制理论的伺服跟踪系统和用神经网络构建的伺服跟踪系统的仿真结果。
The BP neural network PID control method is applied to temperature control system in industry field. The simulation results show that the control method has high control accuracy,...
把BP神经网络的PID控制方法应用到工业领域的温度控制系统中，仿真结果表明：这种控制方法具有较高控制精度和较强的适应性以及良好的控制效果。
The BP neural network PID control method is applied to temperature control system in industry field. The simulation results show that the control method has high control accuracy,...
把BP神经网络的PID控制方法应用到工业领域的温度控制系统中，仿真结果表明：这种控制方法具有较高控制精度和较强的适应性以及良好的控制效果。
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