Bi-directional Long Short-Term Memory using Quantized data of Deep Belief Networks for Sleep Stage Classification

Author:

Yulita Intan Nurma,Fanany Mohamad Ivan,Arymuthy Aniati Murni

Publisher

Elsevier BV

Subject

General Engineering

Reference15 articles.

1. Sleep monitoring using a physiological radar monitoring system integrated with a polysomnography system;Mehran;IEEE Microwave Magazine,2015

2. Islam MZ, Nahiyan KMT, Kiber MA. A motion detection algorithm for video-polysomnography to diagnose sleep disorder,” in Computer and Information Technology. In 18th International Conference on in Computer and Information Technology (ICCIT); 015. p. 272-275.

3. Giri EP, Arymurthy AM, Fanany MI, Wijaya SK. Sleep stages classification using shallow classifiers. In International Conference on Advanced Computer Science and Information Systems (ICACSIS); 2015. p. Sleep stages classification using shallow classifiers.

4. Sleep stage classification using unsupervised feature learning;Längkvist;Advances in Artificial Neural Systems,2012

5. Karpatne A, Atluri G, Faghmous J, Steinbach M, Banerjee A, Ganguly A, et al. Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data. IEEE Transactions on Knowledge and Data Engineering. 2017; PP(99).

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