搜索资源列表
FLch7NNeg1
- 用改进的神经网络MBP算法辨识 ,对具有随机噪声的二阶系统的模型辨识-improved neural network algorithm for identification of MBP, the random noise with the second-order system model
wannnpid532
- 完善网络结构将RBF网络的径向基换成小波函数,调整权值以及公式的变更, 可望在仿真结构中添加非奇异项以验证小波网络的辨识精度和能力,输入层加权值进行调整~..~-to improve the network structure of the RBF network replaced wavelet Radial Basis Functions, value and the right to adjust the formula change, the simulation structure
mbp
- 对具有随机噪声的二阶系统的模型辨识(用改进的神经网络MBP算法辨识)-of random noise with the second-order system model (used to improve the neural network algorithm for identification MBP)
DWD
- 多维非线性辨识的MATLAB程序(用神经网络学习二维非线性函数)-multidimensional nonlinear identification MATLAB (using neural networks to learn two-dimensional nonlinear function)
nnsysid20
- 基于MATLAB的神经网络非线性系统辨识软件包.-MATLAB-based nonlinear neural network system identification package.
bpxtbianshi
- 这是用bp神经网络实现二维系统辨识功能的源程序 -bp neural network function 2D system identification of the source
Adptive
- 神经网络的自适用算法,利用神经网络对系统辨识和跟踪。此程序为c语言和matlab混和编程,由c语言实现算法,由matlab来显示图形。-neural network algorithm applied since the use of neural network system identification and tracking. This procedure c mixed language and Matlab programming, C language algorithms fro
SysIdentify
- 用神经网络对系统辨识(BP网络)。此程序为c语言和matlab混和编程,由c语言实现算法,由matlab来显示图形。-using neural network system identification (BP). This procedure c mixed language and Matlab programming, C language algorithms from Matlab to display graphics.
WORK_final
- 为辨识bmp图像中的数字而设计的系统。它通过对图片的一系列预处理,最后通过神经网络技术识别出图片中显示的数字。-for identification bmp image and the design of digital systems. It adopted a series of photographs of pretreatment, the final neural network technology to identify the pictures show the figures.
nettool
- 基于神经网络的辨识工具箱 (527KB)-Neural Network Based Identification Toolbox (527KB)
EstimationSideslipAngle
- 使用matlab编写的:用神经网络方法来辨识质心侧偏角程序。供大家使用参考。
BPidentify_trymodel
- BP神经网络控制系统辨识的m文件原程序,经过离线训练可以仿真出采样点的变化曲线
MLP
- 本程序实做MLP(Multi-layer perceptron)算法,使用者可以自行设定训练数据集与测试数据集,将训练数据集加载,在2、3维下可以显示其分布状态,并分别设定键节值、学习率、迭代次数来训练其类神经网络,最后可观看辨识率与RMSE(Root Mean squared error)来判别训练是否可以停止。
FLch7NNeg2
- 多维非线性函数辨识的MATLAB程序,用神经网络学习二维非线性函数
BP
- 利用BP网络逼近对象y(k)=u(k)^3+y(k-1)/(1+y(k-1)^2)。采样时间取1ms。输入信号为u(k)=0.5sin(6*pi*t)。(Approximate object y (k), =u (k), ^3+y (k-1) / (1+y (k-1) ^2) using BP networks. Sampling time is 1ms. The input signal is u (k) =0.5sin (6*pi*t).)
corbeppjnd
- 这是一个模型系统辨识的源代码,可以确定过程系统的参数,()
基于最小二乘法RBF神经网络MATLAB程序
- 基于最小二乘法RBF神经网络MATLAB程序,采用最小二乘法及RBF神经网络完成系统辨识(RBF neural network MATLAB program based on least square method, using least square method and RBF neural network to complete system identification)
MATLAB神经网络30个案例分析代码
- 对于神经网络系统辨识,采用MATLAB进行仿真验证(For neural network system identification, MATLAB is used for simulation verification)
chap6
- 神经网络简单介绍,BP神经网络在线和离线辨识,RBF神经自适应控制。(Neural network is introduced simply, BP neural network is identified online and offline, and RBF neural adaptive control.)
基于PD增益自适应调节的模型参考自适应控制
- 基于RBF神经网络辨识的单神经元PID模型参考自适应控制, 基于RBF神经网络辨识的单神经元PID模型参考自适应控制(Single Neuron PID Model Reference Adaptive Control Based on RBF Neural Network Identification)