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
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.
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.
RBFbianshi
- rbf神经网络应用于系统辨识,比BP网络具有较好的泛化能力,学习速度快,辨识效果好!
1
- BP神经网络已广泛应用于非线性建摸、函数逼近、系统辨识等方面，但对实际问题，其模型结构需由 实验确定，无规律可寻。简要介绍了利用 Matlab语言进行 BP网络建立、训练、仿真的方法及注意事项。
identification
- 用神经网络对具有随机噪声的二阶系统模型进行辨识.-Using neural network with random noise of the second-order system identification model.
NN
- 利用神经网络进行系统辨识和逆辨识的程序，可以供大家参考。-The example programme of neural network for system identification and inverse system identification.
chap4_6
- 主要介绍RBF神经网络与PID想结合的辨识系统-Introduces the RBF neural network and PID would like to combine the recognition system
bianshi2
- 一个复杂系统神经网络辨识,采用改进BP算法对随机噪声的二阶系统进行模型辨识,效果挺好的.-A complex neural network system identification, using BP algorithm to improve the random noise of the second-order system identification model, the effect of the good.
wavelet
- 小波神经网络实现非线性系统辨识-non-linear system identification by wavelet
feedback
- 利用神经网络中的elman网络对[-0.5 0.5]间随机信号进行系统辨识-Using elman network in the neural network ，for [-0.5 0.5] between the random signals, system identification
five
- 1.BP神经网络进行模式识别 2.用BP网络对非线性系统进行辨识 3.一个神经网络PID控制器 4.图像处理的PCA算法 5.图像处理的穷举算法-1.BP neural network pattern recognition 2. Using BP network identification of nonlinear systems 3. A neural network PID controller 4. The PCA algorithm for image process
NN_xLMS
- 基于神经网络在线辨识的自适应逆振动控制技术。可以有效地应用到非线性系统的控制。-Line identification based on neural network adaptive inverse vibration control technology. Can be effectively applied to nonlinear system control.
badData
- 基于人工神经网络的电力系统不良数据辨识与修正-bad data detection and identification base on ANN
chap9
- 神经网络控制，基于神经网络的系统辨识，神经网络与其他算法相结合，控制系统的故障诊断-Neural network control, system identification based on neural networks, neural networks combined with other algorithms, control system fault diagnosis
BP_identification
- BP神经网络用于系统辨识的例子，给出了程序和结果-BP network used for system identification
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,()
BP_NNtool
- 能够根据样本数据训练一个很好的网络系统，根据这个系统可以很好的预测数据值(Able to predict data values well based on sample data)