文件名称:NeuralNetwork
- 所属分类：
- 人工智能/神经网络/遗传算法
- 资源属性：
- [Java] [源码]
- 上传时间：
- 2013-11-22
- 文件大小：
- 97kb
- 下载次数：
- 0次
- 提 供 者：
- 陈*
- 相关连接：
- 无
- 下载说明：
- 别用迅雷下载，失败请重下，重下不扣分！
介绍说明－－下载内容均来自于网络，请自行研究使用
该资源是神经网络算法。
ProduceTestFile.jar和src\produce目录下的ProduceTestFile.java用于在画图文件中手写字生成文件后转化成txt文件（生成BPTestFile.txt），注意在画图文件中应将图片大小设为长和宽均为100像素，写字时选择最粗的刷子。
两个txt分别是训练数据和测试数据。读入BPTrainingFile.txt中的样本进行训练，然后用BPTestFile.txt中的样本进行测试。-This resource is neural network algorithm.
The files ProduceTestFile.jar and src\produce\ProduceTestFile.java are used for generatig handwriting drawing files into txt files (BPTestFile.txt). One should pay attention that the document image size should be set to the length and width are both 100 pixels and writing choose the most coarse brush. The two txt files are training data and test data. The program reads BPTrainingFile.txt to train, and then reads BPTestFile.txt to test.
ProduceTestFile.jar和src\produce目录下的ProduceTestFile.java用于在画图文件中手写字生成文件后转化成txt文件（生成BPTestFile.txt），注意在画图文件中应将图片大小设为长和宽均为100像素，写字时选择最粗的刷子。
两个txt分别是训练数据和测试数据。读入BPTrainingFile.txt中的样本进行训练，然后用BPTestFile.txt中的样本进行测试。-This resource is neural network algorithm.
The files ProduceTestFile.jar and src\produce\ProduceTestFile.java are used for generatig handwriting drawing files into txt files (BPTestFile.txt). One should pay attention that the document image size should be set to the length and width are both 100 pixels and writing choose the most coarse brush. The two txt files are training data and test data. The program reads BPTrainingFile.txt to train, and then reads BPTestFile.txt to test.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
NeuralNetwork\.classpath
.............\.project
.............\.settings\org.eclipse.jdt.core.prefs
.............\bin\BackPropagationNeuron.class
.............\...\digits\BackPropagationNeuron.class
.............\...\......\TestBP.class
.............\...\produce\ProduceTestFile.class
.............\...\sample\ColorNet.class
.............\...\......\JColorPreview.class
.............\...\......\Layer.class
.............\...\......\MFrame$1.class
.............\...\......\MFrame$10.class
.............\...\......\MFrame$11.class
.............\...\......\MFrame$12.class
.............\...\......\MFrame$13.class
.............\...\......\MFrame$14.class
.............\...\......\MFrame$15.class
.............\...\......\MFrame$16.class
.............\...\......\MFrame$17.class
.............\...\......\MFrame$18.class
.............\...\......\MFrame$19.class
.............\...\......\MFrame$2.class
.............\...\......\MFrame$20.class
.............\...\......\MFrame$21.class
.............\...\......\MFrame$22.class
.............\...\......\MFrame$3.class
.............\...\......\MFrame$4.class
.............\...\......\MFrame$5.class
.............\...\......\MFrame$6.class
.............\...\......\MFrame$7.class
.............\...\......\MFrame$8.class
.............\...\......\MFrame$9.class
.............\...\......\MFrame.class
.............\...\......\Net.class
.............\...\......\Neuron.class
.............\...\......\Pattern.class
.............\...\TestBP.class
.............\...\TestStruct.class
.............\BPLearningFile.txt
.............\BPTestFile.txt
.............\ProduceTestFile.jar
.............\src\BackPropagationNeuron.java
.............\...\produce\ProduceTestFile.java
.............\...\TestBP.java
.............\...\TestStruct.java
.............\bin\digits
.............\...\produce
.............\...\sample
.............\src\produce
.............\.settings
.............\bin
.............\src
NeuralNetwork