function?[cost?grad?preds]?=?cnnCost（theta?images?labelscnnConfig?meta?pred）
%?Calcualte?cost?and?gradient?for?a?single?layer?convolutional
%?neural?network?followed?by?a?softmax?layer?with?cross?entropy
%?objective.
%????????????????????????????
%?Parameters:
%??theta??????-??a?vector?parameter
%??images?????-??stores?images?in?imageDim?x?imageDim?x?channel?x?numImges
%????????????????array????
%??labels?????-??for?softmax?output?layer?and?cross?entropy?cost?function
%??the?labels?are?the?class?numbers.
%??pred???????-??boolean?only?forward?propagate?and?return
%????????????????predictions
%
%?Returns:
%??cost???????-??cross?entropy?cost
%??grad???????-??gradient?with?respect?to?theta?（if?pred==False）
%??preds??????-??list?of?predictions?for?each?example?（if?pred==True）

if?~exist（‘pred‘‘var‘）
????pred?=?false;
end;



theta?=?thetaChange（thetameta‘vec2stack‘cnnConfig）;
%%======================================================================
%%?STEP?1a:?Forward?Propagation
numlayers?=?size（theta?1）;
numImages?=?size（images4）;
layersizes?=?meta.layersize;



temp?=?cell（numlayers?1）;
grad?=?cell（numlayers?1）;
temp{1}.after?=?images;
assert（isequal（size（images）[layersizes{1}?numImages]）‘layersize?do?not?match?at?layer?1‘）;

for?l?=?2?:?numlayers
????templayer?=?cnnConfig.layer{l};
????tempTheta?=?theta{l};
????switch?templayer.type
????????case?‘conv‘
????????????[temp{l}.after?temp{l}.linTrans]?=?cnnConvolve（temp{l-1}.after?tempTheta.W?tempTheta.b?templayer.nonLinearType?templayer.conMatrix）;?????????
????????case?‘pool‘
????????????[temp{l}.after?temp{l}.weights]?=?cnnPool（templayer.poolDim?temp{l-1}.after?templayer.poolType）;
????????case?‘stack2line‘
????????????temp{l}.after?=?reshape（temp{l-1}.after?[]?numImages）;
????????case?{‘sigmoid‘‘tanh‘‘relu‘‘softmax‘}
????????????temp{l}.after?=?nonlinear（temp{l-1}.after?tempTheta.W?tempTheta.b?templayer.type）;
????????case?‘softsign‘
????????????[temp{l}.after?temp{l}.linTrans]?=?nonlinear（temp{l-1}.after?tempTheta.W?tempTheta.b?templayer.type）;
????end
????assert（isequal（size（temp{l}.after）[layersizes{l}?numImages]）‘layersize?do?not?match?at?layer?%d\n‘l）;
end

%%======================================================================
%%?STEP?1b:?Calculate?Cost
%?Makes?predictions?given?probs?and?returns?without?backproagating?errors.
if?pred
????[~preds]?=?max（temp{numlayers}.after[]1）;
????preds?=?preds‘;
????cost?=?0;
????grad?=?0;
????return;
end;

switch?cnnConfig.costFun
????case?‘crossEntropy‘
????????numClasses?=?cnnConfig.layer{numlayers}.dimension;
????????extLabels?=?zeros（numClasses?numImages）;
????????extLabels（sub2ind（size（extLabels）?labels‘?1?:?numImages））?=?1;
????????cost?=?-?mean（sum（extLabels?.*?log（temp{numlayers}.after）））;
end

%%======================================================================
%%?STEP?1c:?Backpropagation
if?strcmp（cnnConfig.costFun?‘crossEntropy‘）?&&?strcmp（templayer.type?‘softmax‘）
????temp{l}.gradBefore?=?t

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

????.......??????8029??2014-03-16?21:06??0000\cnnCost.m

????.......??????2619??2014-03-16?21:06??0000\cnnInitParams.m

????.......???????826??2014-03-16?21:06??0000\Dataset\MNIST\loadMNISTImages.m

????.......???????516??2014-03-16?21:06??0000\Dataset\MNIST\loadMNISTLabels.m

????.......???7840016??2014-03-16?21:06??0000\Dataset\MNIST\t10k-images-idx3-ubyte

????.......?????10008??2014-03-16?21:06??0000\Dataset\MNIST\t10k-labels-idx1-ubyte

????.......??47040016??2014-03-16?21:06??0000\Dataset\MNIST\train-images-idx3-ubyte

????.......?????60008??2014-03-16?21:06??0000\Dataset\MNIST\train-labels-idx1-ubyte

????.......??????1250??2014-03-16?21:06??0000\DebugTools\computeNumericalGradient.m

????.......??????2647??2014-03-16?21:06??0000\DebugTools\display_network.m

????.......???????679??2014-03-16?21:06??0000\DebugTools\grad_check.m

????.......???????733??2014-03-16?21:06??0000\DebugTools\samplePatches.m

????.......??????2647??2014-03-16?21:06??0000\DebugTools\thetaChange.m

?????文件???????3179??2016-06-02?09:16??0000\Demo\cnnTrain.m

?????文件????????794??2016-05-31?11:20??0000\Demo\config.m

?????文件???????1171??2016-05-11?10:34??0000\Demo\configTestGradient.m

????.......??????3133??2014-03-16?21:06??0000\layer\cnnConvolve.m

????.......??????1403??2014-03-16?21:06??0000\layer\cnnParamsToStack.m

????.......??????2525??2014-03-16?21:06??0000\layer\cnnPool.m

????.......???????988??2014-03-16?21:06??0000\layer\nonlinear.m

????.......??????3956??2014-03-16?21:06??0000\layer\Test.m

????.......???????231??2014-03-16?21:06??0000\layer\TestPool.m

????.......?????18026??2014-03-16?21:06??0000\LICENSE

????.......??????2108??2014-03-16?21:06??0000\README.md

????.......???????102??2014-03-16?21:06??0000\Testing\test.m

????.......??????1718??2014-03-16?21:06??0000\Testing\testGradCom.m

????.......????????93??2014-03-16?21:06??0000\Testing\testInit.m

????.......???????651??2014-03-16?21:06??0000\Testing\testThetaChange.m

????.......??????2538??2014-03-16?21:06??0000\TrainingMethod\minFuncSGD.m

?????目錄??????????0??2014-03-16?21:06??0000\Dataset\MNIST

............此處省略10個文件信息