featureinputlayer and convolution1dlayer

Respuestas (1)

layers = [
featureInputLayer(100,'Name','input')
fullyConnectedLayer(5, 'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','classification')]
layers =
4×1 Layer array with layers: 1 'input' Feature Input 100 features 2 'fc' Fully Connected 5 fully connected layer 3 'sm' Softmax softmax 4 'classification' Classification Output crossentropyex
layers2 = [
featureInputLayer(100,'Name','input')
convolution1dLayer(50, 3,'Stride',1, 'Name','cnn1d')
fullyConnectedLayer(5, 'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','classification')]
layers2 =
5×1 Layer array with layers: 1 'input' Feature Input 100 features 2 'cnn1d' Convolution 3 50 convolutions with stride 1 and padding [0 0] 3 'fc' Fully Connected 5 fully connected layer 4 'sm' Softmax softmax 5 'classification' Classification Output crossentropyex

4 comentarios

san su
san su el 22 de Mzo. de 2022
Thank you for your answer. Many thanks.
My friend run your code, and add "analyzeNetwork(layers2)". There still exist one error.
layers2 = [
featureInputLayer(100,'Name','input')
convolution1dLayer(50, 3,'Stride',1, 'Name','cnn1d')
fullyConnectedLayer(5, 'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','classification')];
analyzeNetwork(layers2)
(非常感谢回答!我朋友跑了下这段程序,添加了analyzeNetwork(layers2),还是报错。见图片。他用featureInputLayer和convolution1dLayer的时候就是这样报错。当时是将多个通道合并,matlab不能合并多个sequenceinputlayer,只能用featureInputLayer。报错显示合并后的维度不满足convolution1dLayer对维度的要求。感觉用的挺别扭。)
yanqi liu
yanqi liu el 22 de Mzo. de 2022
您好,方便的话可以发一下mat数据,有时候网络提示异常不影响训练
san su
san su el 22 de Mzo. de 2022
Editada: san su el 22 de Mzo. de 2022
您好!matlab这个数据要通过arrayDatastore和combine处理下才能训练,也不太好发数据。后来用imageinputlayer代替了featureinputlayer就解决了,不过想要在fullyconnectedlayer后面接convolution1dlayer是不行的。和上面图中的报错一样,程序根本不走。
yanqi liu
yanqi liu el 22 de Mzo. de 2022
是的,如果是做分类,则一般fullyconnectedlayer全连接后就要进入classify了,卷积层一般在中间

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el 20 de Mzo. de 2022

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el 22 de Mzo. de 2022

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