Description: 基于Visual C++6.0的BP神经网络程序,具有可视化界面,可以自由选择输入节点个数,层数,最大迭代次数,步长-Based on Visual C++ 6.0 of BP neural network procedures, with visualization interface, can freely choose the number of input nodes, low-rise, the largest number of iterations, step size Platform: |
Size: 3906560 |
Author:大夹馅 |
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Description: 细胞神经网络(CNN)GUI源代码
细胞神经网络(CNN)是一种和人类神经网络非常相似的并行计算模型,各个邻接节点间有不同的通信。在本程序中A模型是反馈矩阵,B是控制矩阵。
-Cellular neural network (CNN) GUI source code for cellular neural network (CNN) is a human neural network is very similar to the parallel computing model, all adjacent nodes have different communication. In this process, the feedback matrix A model, B is the control matrix. Platform: |
Size: 51200 |
Author:lcp |
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Description: 神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例-Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input vector to solve more complex classification problems, based on the perceptron neural network to deal with complex classification problems, numerical analysis matlab-GUI, using BP network function source approximation, self-organizing feature map application Platform: |
Size: 41984 |
Author:stephen |
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Description: 神经网络matlab代码。有GUI界面实现和讲解,很强大-Neural network matlab code. There are GUI interfaces to achieve and explain the very strong Platform: |
Size: 1027072 |
Author:rensu |
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Description: 使用MATLAB GUI编写的有界面的神经网络分类的方法。适合做课程设计-The preparation of the use of MATLAB GUI interface of the method of neural network classification. Suitable for curriculum design Platform: |
Size: 1306624 |
Author:lixiaodong |
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Description: 结合Matlab的GUI和神经网络开发出来的界面-Combination of Matlab' s GUI and neural network developed interface Platform: |
Size: 48128 |
Author:thomas |
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Description: this MLP project in Neural Network that have userinterface. run GUI.m to execute project -this is MLP project in Neural Network that have userinterface. run GUI.m to execute project Platform: |
Size: 24576 |
Author:autstudent |
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Description: Project with GUI for door and other rectangular objects. Uses hough transform and neural-network based recognition. (MATLAB r2007b) Platform: |
Size: 8200192 |
Author:Alex |
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Description: CNN Class, ver 0.72.
Change log:
Ver 0.72:
Sample GUI added, demonstrating use of convolutional network for handwriten digits recognition.
Training runs 20 faster.
Ver 0.71:
Bug fix: training was stoped after 1 epoch.
Ver 0.70:
First release.
This project provides matlab class for implementation of convolutional neural networks. -CNN Class, ver 0.72.
Change log:
Ver 0.72:
Sample GUI added, demonstrating use of convolutional network for handwriten digits recognition.
Training runs 20 faster.
Ver 0.71:
Bug fix: training was stoped after 1 epoch.
Ver 0.70:
First release.
This project provides matlab class for implementation of convolutional neural networks. Platform: |
Size: 555008 |
Author:narendra |
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Description: design and implementation of feedforward neural network with BP training algorithm.(include the GUI) Platform: |
Size: 564224 |
Author:maisam |
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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: 针对BP神经网络算法,使用MATLAB软件进行了编译,并给出了BPGUI的模型例子(An example of the GUI interface of BP neural network algorithm) Platform: |
Size: 75776 |
Author:visdo |
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Description: 本课题为基于MATLAB的BP神经网络手写数字识别系统。带有GUI人机交互式界面。读入测试图片,通过截取某个数字,进行预处理,经过bp网络训练,得出识别的结果。可经过二次改造成识别中文汉字,英文字符等课题。(This project is based on Matlab bp neural network Handwritten digit recognition system. With GUI human-computer interactive interface. Read in the test picture, through the interception of a number, preprocessing, after BP network training, get the recognition results. It can be transformed to recognize Chinese characters and English characters.) Platform: |
Size: 542720 |
Author:www.wobishe.com |
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