Description: Stacked self classification, deep learning algorithm code signal contains examples for classification and recognition of action.
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stackedae_exercise\checkStackedAECost.m
stackedae_exercise\computeNumericalGradient.m
stackedae_exercise\display_network.m
stackedae_exercise\feedForwardAutoencoder.m
stackedae_exercise\initializeParameters.m
stackedae_exercise\loadMNISTImages.m
stackedae_exercise\loadMNISTLabels.m
stackedae_exercise\params2stack.m
stackedae_exercise\softmaxCost.m
stackedae_exercise\softmaxPredict.m
stackedae_exercise\softmaxTrain.m
stackedae_exercise\sparseAutoencoderCost.m
stackedae_exercise\stack2params.m
stackedae_exercise\stackedAECost.m
stackedae_exercise\stackedAEExercise.m
stackedae_exercise\stackedAEPredict.m
stackedae_exercise\t10k-images.idx3-ubyte
stackedae_exercise\t10k-labels.idx1-ubyte
stackedae_exercise\train-images.idx3-ubyte
stackedae_exercise\train-labels.idx1-ubyte
stackedae_exercise\minFunc\ArmijoBacktrack.m
stackedae_exercise\minFunc\autoGrad.m
stackedae_exercise\minFunc\autoHess.m
stackedae_exercise\minFunc\autoHv.m
stackedae_exercise\minFunc\autoTensor.m
stackedae_exercise\minFunc\callOutput.m
stackedae_exercise\minFunc\conjGrad.m
stackedae_exercise\minFunc\dampedUpdate.m
stackedae_exercise\minFunc\example_minFunc.m
stackedae_exercise\minFunc\example_minFunc_LR.m
stackedae_exercise\minFunc\isLegal.m
stackedae_exercise\minFunc\lbfgs.m
stackedae_exercise\minFunc\lbfgsC.c
stackedae_exercise\minFunc\lbfgsC.mexa64
stackedae_exercise\minFunc\lbfgsC.mexglx
stackedae_exercise\minFunc\lbfgsC.mexmac
stackedae_exercise\minFunc\lbfgsC.mexmaci
stackedae_exercise\minFunc\lbfgsC.mexmaci64
stackedae_exercise\minFunc\lbfgsC.mexw32
stackedae_exercise\minFunc\lbfgsC.mexw64
stackedae_exercise\minFunc\lbfgsUpdate.m
stackedae_exercise\minFunc\mchol.m
stackedae_exercise\minFunc\mcholC.c
stackedae_exercise\minFunc\mcholC.mexmaci64
stackedae_exercise\minFunc\mcholC.mexw32
stackedae_exercise\minFunc\mcholC.mexw64
stackedae_exercise\minFunc\mcholinc.m
stackedae_exercise\minFunc\minFunc.m
stackedae_exercise\minFunc\minFunc_processInputOptions.m
stackedae_exercise\minFunc\polyinterp.m
stackedae_exercise\minFunc\precondDiag.m
stackedae_exercise\minFunc\precondTriu.m
stackedae_exercise\minFunc\precondTriuDiag.m
stackedae_exercise\minFunc\rosenbrock.m
stackedae_exercise\minFunc\taylorModel.m
stackedae_exercise\minFunc\WolfeLineSearch.m
stackedae_exercise\minFunc\logistic\LogisticDiagPrecond.m
stackedae_exercise\minFunc\logistic\LogisticHv.m
stackedae_exercise\minFunc\logistic\LogisticLoss.m
stackedae_exercise\minFunc\logistic\mexutil.c
stackedae_exercise\minFunc\logistic\mexutil.h
stackedae_exercise\minFunc\logistic\mylogsumexp.m
stackedae_exercise\minFunc\logistic\repmatC.c
stackedae_exercise\minFunc\logistic\repmatC.dll
stackedae_exercise\minFunc\logistic\repmatC.mexglx
stackedae_exercise\minFunc\logistic\repmatC.mexmac
stackedae_exercise\数据\cs.mat
stackedae_exercise\数据\cs2.mat
stackedae_exercise\数据\cs4.mat
stackedae_exercise\数据\tl.mat
stackedae_exercise\数据\tl2.mat
stackedae_exercise\数据\tl3.mat
stackedae_exercise\数据\tl4.mat
stackedae_exercise\数据\TZ.mat
stackedae_exercise\时域特征\(IAV+RMS).mat
stackedae_exercise\时域特征\(IAV+RMS)nor.mat
stackedae_exercise\时域特征\AllIAV.mat
stackedae_exercise\时域特征\AllRMS.mat
stackedae_exercise\时域特征\cs(IAV+RMS).mat
stackedae_exercise\时域特征\cs(IAV+RMS)nor.mat
stackedae_exercise\时域特征\csIAV.mat
stackedae_exercise\时域特征\csIAVnor.mat
stackedae_exercise\时域特征\csRMS.mat
stackedae_exercise\时域特征\csRMSnor.mat
stackedae_exercise\时域特征\IAV.mat
stackedae_exercise\时域特征\IAVnor.mat
stackedae_exercise\时域特征\RMS.mat
stackedae_exercise\时域特征\RMSnor.mat
stackedae_exercise\频域特征\(MPF+MF).mat
stackedae_exercise\频域特征\(MPF+MF)nor.mat
stackedae_exercise\频域特征\AllMF.mat
stackedae_exercise\频域特征\AllMPF.mat
stackedae_exercise\频域特征\cs(MPF+MF).mat
stackedae_exercise\频域特征\cs(MPF+MF)nor.mat
stackedae_exercise\频域特征\csMF.mat
stackedae_exercise\频域特征\csMFnor.mat
stackedae_exercise\频域特征\csMPF.mat
stackedae_exercise\频域特征\csMPFnor.mat
stackedae_exercise\频域特征\MF.mat
stackedae_exercise\频域特征\MFnor.mat