首页自定义激活函数替换卷积神经网络relulayer的matlab代码

自定义激活函数替换卷积神经网络relulayer的matlab代码

时间: 2023-11-21 22:03:14 浏览: 241

以下是一个示例代码，用于将ReLU激活函数替换为sigmoid激活函数： ```matlab classdef SigmoidLayer < nnet.layer.Layer properties % (Optional) Layer properties. % 例如： % Layer properties can be set and used during training and prediction. % MyProperty end methods function layer = SigmoidLayer(name) % (Optional) Create a myLayer. % This function must have the same name as the class. % 例如： % layer = myLayer(myProperty) % Set layer name. layer.Name = name; % (Optional) Set layer description. layer.Description = 'Sigmoid Layer'; end function Z = predict(layer, X) % Forward input data through the layer and output the result. % 例如： % Z = layer.predict(X) % Z = mySigmoidFunction(X) Z = sigmoid(X); end function [dLdX] = backward(layer, X, Z, dLdZ, memory) % Backward propagate the derivative of the loss function through % the layer. % 例如： % dLdX = layer.backward(X, Z, dLdZ, memory) % dLdX = mySigmoidFunctionGradient(X, Z, dLdZ) dLdX = dLdZ .* Z .* (1-Z); end end end ``` 然后，您可以将它与卷积神经网络的各层结合使用，例如： ```matlab layers = [ imageInputLayer([28 28 1]) convolution2dLayer(5,20) SigmoidLayer('sigmoid1') maxPooling2dLayer(2,'Stride',2) convolution2dLayer(5,50) SigmoidLayer('sigmoid2') maxPooling2dLayer(2,'Stride',2) fullyConnectedLayer(500) SigmoidLayer('sigmoid3') fullyConnectedLayer(10) softmaxLayer classificationLayer]; options = trainingOptions('sgdm',... 'MaxEpochs',20,... 'InitialLearnRate',0.01); net = trainNetwork(trainData,layers,options); ```

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