其中的SIMULINK工具箱可以模拟线性或非线性、连续或离散或两者的混合系统，对复杂的非线性系统仿真模拟的效果更为明显。
SIMULINK toolbox which can simulate the linear or nonlinear, continuous or discrete, or both of the hybrid systems, nonlinear system of complex simulation of the effect becomes more apparent.
本文论述了EWB仿真软件的优点，分析了EWB在《信号与线性系统》课程中的应用及其对教学方法的影响。
The article discusses advantages of EWB and analyzes EWB applied to Signal and Linearity System. At the same time, EWB has influenced upon teaching means greatly.
Matlab是一种功能极强的线性系统分析和仿真工具，其数值的计算能力和数据的可视化能力极强。
MATLAB is a powerful tool for analyzing and stimulating the linear system and has very strong ability for calculating and visualizing data.
实验结果表明，在非线性系统模型的仿真中，贝叶斯预测滤波框架能够较好的实现对简单物体运动的跟踪和方位的预测。
The results show that in the simulation of non-linear system model, this framework for Bayesian predictive filter can implement the tracking of simple motion and the orientation prediction.
仿真结果表明，在没有被控对象先验知识的情况下，利用该方法能准确地建立连续非线性系统的逆模型。
Simulation results show that the presented method can accurately construct the inverse dynamic model of the continuous nonlinear system even without prior knowledge about the controlled plant.
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。
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.
使用电路仿真软件对非线性系统模型进行电路仿真计算，给出了参数设置和搭建电路的步骤。
The nonlinear model is simulated with the electronic simulation software, and the approaches of building electronic circuit and setting parameters is also presented.
仿真结果表明，用GMDH方法建立非线性系统模型，具有预测精度高、计算稳定性好等优点。
Simulation result shows that GMDH method can be applied to nonlinear system modeling successfully and has such advantages as higher prediction precision and good calculation stability, etc.
以船舶发电机这一大型非线性系统为例，对其进行混沌神经网络仿真建模研究，提出了用混沌神经网络仿真建模的一般思路和方法。
A general idea and a basic method for modeling with neural networks are put forward on the basis of the study of Marine synchronous generator modeling based on chaotic neural networks.
提出了一种基于遗传算法的非线性系统参数仿真优化方法，解决了非线性系统参数优化问题。
In this paper, an optimization method of non - lineal system parameters based on genetic algorithms is presented which solves the problem of parameter optimization in non - lineal systems.
将该辨识器用于一类非线性系统的模糊辨识，仿真结果验证了所提出方法的有效性。
The identifier is applied to the fuzzy identification for a class of nonlinear systems, and the simulation results demonstrate the effectiveness of the proposed identification methods.
仿真结果表明，这种策略既提高了系统的鲁棒性和控制精度，又解决了非线性系统滑模面不易构造的难题。
The simulation results indicate that the presented strategy has not only promoted the system to be more robust and precise, also solved the problem of constructing the nonlinear sliding surfaces.
通过一个非线性实例设计了它的自适应神经网络模糊模型，从仿真结果可看出改进后的非线性系统模型更有效。
By designing a self-adapt neural fuzzy model for a nonlinear system, we can draw a conclusion that the new nonlinear model has high precision and good visual effect.
通过一个非线性实例设计了它的自适应神经网络模糊模型，从仿真结果可看出改进后的非线性系统模型更有效。
By designing a self-adapt neural fuzzy model for a nonlinear system, we can draw a conclusion that the new nonlinear model has high precision and good visual effect.
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