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Efficient ECG Signal Compression Using CAE by sunilkumarkn26 is a document available to read on EtoBox.
What is Efficient ECG Signal Compression Using CAE about?
The document discusses using a deep convolutional autoencoder model to compress ECG signals. It proposes a 27-layer deep network with encoder and decoder parts to compress ECG data into low-dimensional vectors and then reconstruct the signals. The model is evaluated on a dataset of 4800 ECG fragments from 48 patients, achieving a 32.25 compression rate and average 2.73% PRD, suggesting it can allow secure low-dimensional data transfer for remote healthcare.
- Author
- sunilkumarkn26
- Language
- EN