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2下载：
这是一个用matlab实现的RBF神经网络手写数字识别算法.此算法加入相应的手写数字图后可以运行.-This is a realization of using Matlab RBF neural network recognition algorithm handwritten figures. This algorithm adherence to the corresponding figures handwritten map after the run.
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基于BP神经网络的手写体数字识别程序，使用matlab开发-based Neural Network handwritten numeral recognition, the use of Matlab development
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MATLAB 神经网络用于数字识别源程序 手写数字识别-MATLAB neural network for digital identification of the source handwritten numeral recognition
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基于BP神经网络的手写体数字识别程序，使用matlab开发-BP neural network based on handwritten digit recognition program, developed using matlab
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基于BP神经网络的手写数字识别系统，基于Matlab开发，实现手写输入板功能，特征提取，模型训练，手写识别等功能。详细使用方法在readme说明文档中。-Handwritten numeral recognition system based on BP neural network, developed based on Matlab, handwriting input board, feature extraction, model training, handwriting recogn
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基于神经网络的手写体数字识别，它是用matlab实现的，其中用3种不同的神经的网络方法实现了手写体数字的识别，非常利于初学者的学习和交流。-Handwritten digit recognition based on neural networks, which is achieved using matlab, in which three different neural network to achieve the recognition of handwritten digits, is
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手写数字的识别的matlab实现，运用基本的图像处理和BP神经网络来实现，程序的使用方法请参阅 readme.txt-Handwritten digit recognition matlab realize, the use of basic image processing and BP neural network to achieve the program' s usage, please refer to the readme.txt
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This project provides matlab class for implementation of convolutional neural networks. This networks was developed by Yann LeCun and have sucessfully used in many practical applications, such as handwritten digits recognition, face detection, robot
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用matlab实现的神经网络经过训练，实现手写数字是别的-Using matlab neural network trained to achieve something else handwritten digits
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基于概率神经网络的手写体数字识别，matlab实现，非常好的程序-Handwritten numeral recognition, probabilistic neural network based on MATLAB, a very good program
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a good document about Neural networks and CHARACTER RECOGNITION Handwritten character Recognition: Training a Simple NN for classification using MATLAB
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神经网络的手写 数字识别matlab。包含数据库，可直接运行。-Handwritten numeral recognition matlab neural network.Contains a , can be directly run
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Andrew Ng Cousera 机器学习课程神经网络手写字符识别，源代码以及说明文档(Andrew Ng Cousera 's Machine learning courses, Neural Network handwritten character recognition, source code and documentation)
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BP神经网络实现手写数字识别matlab实现(Matlab implementation of handwritten digit recognition based on BP neural network)
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基于神经网络识别的手写数字识别系统，有gui界面(Handwritten digital recognition system based on neural network recognition)
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bayes和神经网络的手写体数字识别程序（matlab）(bayes and neural network handwritten numeral recognition program (matlab))
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基于BP神经网络手写数字识别，main函数是主函数，识别的成功率在86%左右。(Based on the BP Neural Network handwritten digital recognition, the main function is the main function, and the recognition success rate is about 86%.)
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基于神经网络及GUI触摸板的手写数字识别，基本的机器学习例子(Handwritten numerals recognition based on neural network and GUI touch board, basic machine learning examples)
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BP神经网络基本原理概述：这种网络模型利用误差反向传播训练算法模型，能够很好地解决多层网络中隐含层神经元连接权值系数的学习问题，它的特点是信号前向传播、误差反向传播，简称BP（Back Propagation）神经网络。BP学习算法的基本原理是梯度最快下降法，即通过调整权值使网络总误差最小，在信号前向传播阶段，输入信号经输入层处理再经隐含层处理最后传向输出层处理；在误差反向传播阶段，将输出层输出的信号值与期望输出信号值比较得到误差，若误差较大则把误差信号传回隐含层直至输入层，在各层神经元中使用
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How to run the program
1. open MATLAB goto the project's root path
2. run main.m
3. in the command window it will show the accuracy calculated by testing data set
4. press any key in the command window to show the GUI for this project
5. click t
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