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matlab补偿模糊神经网络源代码
本文中有两个函数m文件:model126.m是一个用于预测的完全没有用工具箱函数的补偿模糊神经网络主程序,用于仿真、对比训练数据和网络输出的差异;cb.m是一个非线性系统的数学模型,在model126.m中用“ode45”函数求解这个数学模型后,可以得到105个x1(t)、x2(t)和y(t),从而建立起一个两输入一输出的补偿模糊神经网络。(There are two function m file in this paper: model126.m is a completely useless for predicting the compensation fuzzy neural network toolbox function for the main program, the difference between the simulation and contrast the training data and the output of the network; cb.m is a mathematical model of a nonlinear system, using the "ode45" function to solve the mathematical model in the model126.m after that can be 105 X1 (T), X2 (T) and Y (T), which established a two input and one output fuzzy neural network.)
本文中有两个函数m文件:model126.m是一个用于预测的完全没有用工具箱函数的补偿模糊神经网络主程序,用于仿真、对比训练数据和网络输出的差异;cb.m是一个非线性系统的数学模型,在model126.m中用“ode45”函数求解这个数学模型后,可以得到105个x1(t)、x2(t)和y(t),从而建立起一个两输入一输出的补偿模糊神经网络。(There are two function m file in this paper: model126.m is a completely useless for predicting the compensation fuzzy neural network toolbox function for the main program, the difference between the simulation and contrast the training data and the output of the network; cb.m is a mathematical model of a nonlinear system, using the "ode45" function to solve the mathematical model in the model126.m after that can be 105 X1 (T), X2 (T) and Y (T), which established a two input and one output fuzzy neural network.)
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下载文件列表
文件名 | 大小 | 更新时间 |
---|---|---|
model126.m | 3129 | 2008-11-29 |
cb.m | 120 | 2008-11-08 |