Description: 这是一个matlab实现第归神经网络的例子, 实现的第归神经网络是 : Real Time Recurrent Learning-This is a Matlab achieve its neural network naturalization example, the realization of naturalization neural network is : Real Time Learning Recurrent Platform: |
Size: 5120 |
Author:王世海 |
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Description: two Matlab functions for initializing and training a recurrent neural network -two Matlab functions for initializing and training a recurrent neural network Platform: |
Size: 4096 |
Author:william |
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Description: 回声状态神经网络(ESN)是一种性能优异的递归神经网络,已经在各领域广泛研究,这是ESN的发明人研制的MATLAB工具箱,可供有关人员参考使用-Echo state neural networks (ESN) is a performance of recurrent neural networks have been extensively studied in various fields, which is ESN inventor developed MATLAB toolbox, use and reference available to the persons Platform: |
Size: 101376 |
Author:xu mark |
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Description: 递归神经网络程序,用于递归神经网络的训练,并可以进行泛化。-Recurrent neural network procedure for recurrent neural network training and generalization can be carried out. Platform: |
Size: 1024 |
Author:杨丽 |
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Description: 给于MATLAB 环境下的非线性滤波器。此设计中用到了,混合网络建模。B样条网络和对角递归神经元网络。-In the MATLAB environment to the non-linear filter. This design used a mixed network modeling. B-spline network and on the diagonal recurrent neural network. Platform: |
Size: 8192 |
Author:庞宇 |
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Description: Program for training and testing the Elman Recurrent Neural Network model when used to predict Platform: |
Size: 1024 |
Author:Abd Kadir |
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Description: 此包含有遗传算法、粒子群算法、BP算法优化对角递归神经网络的MATLAB程序-This includes genetic algorithms, particle swarm optimization, BP algorithm for diagonal recurrent neural network of the MATLAB program Platform: |
Size: 134144 |
Author: |
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Description: a transmission line fault location model which is based on an Elman recurrent network
(ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with
different inception times are implemented on a 380-kV prototype power system. Wavelet transform
(WT) is used for selecting distinctive features about the faulty signals. The system has the advantages of
utilizing single-end measurements, using both voltage and current signals. ERN is able to determine the
fault location occurred on transmission line rapidly and correctly as an important alternative to standard
feedforward back propagation networks (FFNs) and radial basis functions (RBFs) neural networks. Platform: |
Size: 761856 |
Author:charlie |
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Description: RNNSIM ver. 1.0 is a program with an intercative graphical user interface
(GUI) that runs under MATLAB ver. 5.0 or higher. The program can be used
in training and testing the Random Neural Network(RNN) models.
This version (ver. 1.0) implements only the 3 layer feed forward RNN model.
In the next versions, the multi hidden layers and the recurrent RNN models
can be implemented. To obtain faster training, the training section can be
written as a MEX file and invoked from the GUI.
If you have the m files in the directory rnnsim for example, then you can
run the program following the next steps:
1- run MATLAB as usual
2- from the MATLAB command window, write cd rnnsim
3- from the MATLAB command window, write rnnsim- RNNSIM ver. 1.0 is a program with an intercative graphical user interface
(GUI) that runs under MATLAB ver. 5.0 or higher. The program can be used
in training and testing the Random Neural Network(RNN) models.
This version (ver. 1.0) implements only the 3 layer feed forward RNN model.
In the next versions, the multi hidden layers and the recurrent RNN models
can be implemented. To obtain faster training, the training section can be
written as a MEX file and invoked from the GUI.
If you have the m files in the directory rnnsim for example, then you can
run the program following the next steps:
1- run MATLAB as usual
2- from the MATLAB command window, write cd rnnsim
3- from the MATLAB command window, write rnnsim
Platform: |
Size: 63488 |
Author:hacen |
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Description: This paper describes a Model Reference Adaptive
System (MRAS) based scheme using a multilayer
Recurrent Neural Network (RNN) for online speed
estimation of sensorless vector controlled inductmon
motor drive.
Platform: |
Size: 11264 |
Author:chinni |
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Description: 这是一个四个不同的S函数实现集合的递归模糊神经网络(RFNN)。该网络采用了4组可调参数,这使得它非常适合在线学习/操作,从而可应用到系统识别等方面。-This is a collection of four different S-function implementations of the recurrent fuzzy neural network (RFNN) described in detail in [1]. It is a four-layer, neuro-fuzzy network trained exclusively by error backpropagation at layers 2 and 4. The network employs 4 sets of adjustable parameters. In Layer 2: mean[i,j], sigma[i,j] and Theta[i,j] and in Layer 4: Weights w4[m,j]. The network uses considerably less adjustable parameters than ANFIS/CANFIS and therefore, its training is generally faster. This makes it ideal for on-line learning/operation. Also, its approximating/mapping power is increased due to the employment of dynamic elements within Layer 2. Scatter-type and Grid-type methods are selected for input space partitioning. Platform: |
Size: 117760 |
Author:林真天 |
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Description: 利用MATLAB实现循环神经网络的例子,便于大家更好的理解循环神经网络RNN的原理。(The example of recurrent neural network is implemented by MATLAB, so that you can have a better understanding of the principle of recurrent neural network RNN.) Platform: |
Size: 1024 |
Author:WG_JNU |
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