搜索资源列表
BP
- 使用BP网络逼近非线性函数,可以获得很不错的逼近效果！
BP_tanh_linaer
- BP神经网络Simulink模型。。例子给了个离散传递函数。训练后的网络可以逼近任意传递函数，或者非线性函数。-Simulink model of BP neural network. . Examples for the discrete transfer function. Trained network can approximate any transfer function, or the nonlinear function.
threeneuralnetword
- 如何构造神经网络，及构造一个三层前馈神经网络，来逼近非线性函数-How to construct a neural network, and construct a three-layer feedforward neural network to approximate nonlinear functions
bp
- 用bp人工神经网络来逼近非线性函数-With bp artificial neural network to approximate nonlinear functions. . . . . .
bp
- 基于BP神经网络算法的函数逼近，利用matlab实现BP算法逼近任意非线性函数-BP neural network algorithm based on function approximation, using matlab to achieve BP algorithm approximate any nonlinear function
bp-rbf-neural-networks
- 介绍如何通过matlab使用bp神经网络和rbf神经网络来逼近非线性函数-Describes how to use matlab bp neural network and rbf neural networks to approximate nonlinear functions
PID-self-tuning-of-parameters
- 本文把神经网络技术应用在PID控制中，充分利用神经网络具有非线性函数逼近能力构造神经网络PID自整定控制器。-This paper, the neural network technology used in PID control, the full use of neural network structure with nonlinear function approximation capability PID self-tuning neural network controller.
RBF
- 运用常规的PID控制算法很难达到人们所要求的控制效果。采用改进的BP神经网络算法进行改进具有以任意精度逼近非线性函数的能力，而且通过它的自身的学习，可以找到某一最优控制率下的PID控制器参数，使其具有更好的鲁棒性和自适应的能力。-Using conventional PID control algorithm is difficult to live up to the required control effect. The improved BP neural network algorit
bpok
- 用人工神经元网络训练输入来逼近已知非线性函数。-To approximate the known nonlinear function with the Artificial Neural Network
M
- bp算法逼近非线性函数，利用bp算法逼近单输入函数-Bp algorithm approximating function
BP1
- 采用BP神经网络逼近非线性函数,matlab源码实现，易于初学者理解，简单实用。-nonliear function by BP network approximatinon
bp-artifical-netwok
- bp人工神经网络，要逼近非线性函数，并给出拟合效果-bp artifical nerual network
BP
- 基于BP神经网络算法的函数逼近，根据BP神经网络算法的原理，编写Matlab程序，逼近非线性函数。-Function approximation based on BP neural network algorithm to approximate nonlinear functions, according to the principle of BP neural network algorithm, written Matlab program.
BPbijin
- 自己写的BP网络逼近非线性函数的matlab的m文件，没有调用matlab现成的函数-Write your own BP neural network nonlinear function approximation matlab m-file, there is no ready-made call matlab function
BP
- BP神经网络 搭建神经网络来逼近非线性函数-BP neural network to build a neural network to approximate nonlinear functions
9GAP
- 使用BP算法逼近非线性函数，没有使用神经网络工具箱，适合初学者。-Using BP neural network approximation of nonlinear function, there is no use of neural network toolbox, suitable for beginners.
main
- 应用BP神经网络逼近非线性函数，非线性函数为多输入单输出，逼近误差<5 ，采用经典的BP算法。-Application of BP neural network to approximate nonlinear function, nonlinear function for multiple input and single output, the approximation error < 5 , using the classic BP algorithm.
BP
- BP神经网络经过训练与学习，逼近非线性函数(BP neural networks are trained and studied to approximate nonlinear functions)
CMAC逼近非线性函数
- 利用小脑模型神经网络逼近非线性函数，MATLAB编写m文件实现，给出逼近误差(Cerebellar model neural network is used to approximate nonlinear functions. MATLAB is used to write M files, and approximation error is given.)
RBF神经网络逼近非线性函数
- 利用径向基神经网络逼近非线性函数，MATLAB编程实现，给出训练误差(Radial basis function neural network is used to approximate nonlinear functions. MATLAB programming is implemented to give training error.)