文件名称:cnn
- 所属分类：
- 图形图像处理(光照,映射..)
- 资源属性：
- [Matlab] [源码]
- 上传时间：
- 2016-08-24
- 文件大小：
- 8.78mb
- 下载次数：
- 0次
- 提 供 者：
- l**
- 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
卷积神经网络的实现代码，包括训练，测试，SGD随机梯度下降法等功能。-Convolution neural network implementation code, including training, testing, SGD stochastic gradient descent and other functions.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
cnn\cnnConvolve.m
...\cnnCost.m
...\cnnExercise.m
...\cnnInitParams.m
...\cnnParamsToStack.m
...\cnnPool.m
...\cnnTrain.m
...\.ommon\display_network.m
...\......\loadMNISTImages.m
...\......\loadMNISTLabels.m
...\......\minFunc_2012\autoDif\autoGrad.m
...\......\............\.......\autoHess.m
...\......\............\.......\autoHv.m
...\......\............\.......\autoTensor.m
...\......\............\.......\derivativeCheck.m
...\......\............\.......\fastDerivativeCheck.m
...\......\............\example_derivativeCheck.m
...\......\............\example_minFunc.m
...\......\............\logisticExample\example_minFunc_LR.m
...\......\............\...............\LogisticDiagPrecond.m
...\......\............\...............\LogisticHv.m
...\......\............\...............\LogisticLoss.m
...\......\............\...............\mylogsumexp.m
...\......\............\mexAll.m
...\......\............\.inFunc\ArmijoBacktrack.m
...\......\............\.......\compiled\lbfgsAddC.mexa64
...\......\............\.......\........\lbfgsAddC.mexmaci64
...\......\............\.......\........\lbfgsAddC.mexw64
...\......\............\.......\........\lbfgsC.mexa64
...\......\............\.......\........\lbfgsC.mexglx
...\......\............\.......\........\lbfgsC.mexmac
...\......\............\.......\........\lbfgsC.mexmaci
...\......\............\.......\........\lbfgsC.mexmaci64
...\......\............\.......\........\lbfgsC.mexw32
...\......\............\.......\........\lbfgsC.mexw64
...\......\............\.......\........\lbfgsProdC.mexa64
...\......\............\.......\........\lbfgsProdC.mexmaci64
...\......\............\.......\........\lbfgsProdC.mexw64
...\......\............\.......\........\mcholC.mexa64
...\......\............\.......\........\mcholC.mexglx
...\......\............\.......\........\mcholC.mexmac
...\......\............\.......\........\mcholC.mexmaci64
...\......\............\.......\........\mcholC.mexw32
...\......\............\.......\........\mcholC.mexw64
...\......\............\.......\conjGrad.m
...\......\............\.......\dampedUpdate.m
...\......\............\.......\isLegal.m
...\......\............\.......\lbfgs.m
...\......\............\.......\lbfgsAdd.m
...\......\............\.......\lbfgsProd.m
...\......\............\.......\lbfgsUpdate.m
...\......\............\.......\mchol.m
...\......\............\.......\mcholinc.m
...\......\............\.......\.ex\lbfgsAddC.c
...\......\............\.......\...\lbfgsC.c
...\......\............\.......\...\lbfgsProdC.c
...\......\............\.......\...\mcholC.c
...\......\............\.......\minFunc.m
...\......\............\.......\minFunc_processInputOptions.m
...\......\............\.......\polyinterp.m
...\......\............\.......\precondDiag.m
...\......\............\.......\precondTriu.m
...\......\............\.......\precondTriuDiag.m
...\......\............\.......\taylorModel.m
...\......\............\.......\WolfeLineSearch.m
...\......\............\rosenbrock.m
...\......\samplePatches.m
...\computeNumericalGradient.m
...\loadMNISTImages.m
...\minFuncSGD.m
...\train-images.idx3-ubyte
...\common\minFunc_2012\minFunc\compiled
...\......\............\.......\mex
...\......\............\autoDif
...\......\............\logisticExample
...\......\............\minFunc
...\......\minFunc_2012
...\common
cnn