Feature Extraction using deep autoencoder

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Satz92
Satz92 2018 年 12 月 19 日
編集済み: arahiche 2023 年 9 月 28 日
I have filtered my ecg signal of 108000*1 length and then divided into blocks using window size of 64 samples each. Now i need to extract feature from each window using deep autoencoder in MATLAB. any help or idea how can i perform this? Thanks in advance.

回答 (1 件)

BERGHOUT Tarek
BERGHOUT Tarek 2019 年 4 月 11 日
1) you must create a data set of this windows , dataset =[window1;window2; window3 ...................].
2) train these dataset with an AES.
3) the hidden layer will be your new extructed dataset;
  2 件のコメント
Shankar Parmar
Shankar Parmar 2022 年 3 月 4 日
Sir,
How can I extract this Hidden Layer in MATLAB using
trainAutoencoder command.
arahiche
arahiche 2023 年 9 月 28 日
編集済み: arahiche 2023 年 9 月 28 日
To access the extracted features you need to use encode function.
here is an example;
hiddenSize = 100; % for example
AE_model = trainAutoencoder(Input_data,hiddenSize);
% you can view you model using this function
view(AE_model)
% To access the latent code generated
features = encode(AE_model,Input_data);

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