Arrhythmia Classification in Multi-Channel ECG Signals Using Deep Neural Networks
Kyungna Kim
EECS Department, University of California, Berkeley
Technical Report No. UCB/EECS-2018-80
May 19, 2018
http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-80.pdf
Advisors: Stuart J. Russell
BibTeX citation:
@mastersthesis{Kim:EECS-2018-80, Author= {Kim, Kyungna}, Title= {Arrhythmia Classification in Multi-Channel ECG Signals Using Deep Neural Networks}, School= {EECS Department, University of California, Berkeley}, Year= {2018}, Month= {May}, Url= {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-80.html}, Number= {UCB/EECS-2018-80}, }
EndNote citation:
%0 Thesis %A Kim, Kyungna %T Arrhythmia Classification in Multi-Channel ECG Signals Using Deep Neural Networks %I EECS Department, University of California, Berkeley %D 2018 %8 May 19 %@ UCB/EECS-2018-80 %U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2018/EECS-2018-80.html %F Kim:EECS-2018-80