Electrocardiogram beat classification based on wavelet transformation and probabilistic neural network
By Sung-Nien Yu, Ying-Hsiang Chen. Pattern Recognition Letters, 2007
295 citations recorded by the source corpus.
Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Pulmonary and Respiratory Medicine
View Paper: https://www.semanticscholar.org/paper/de16248d94ea3d44f352a1f227dac38c51e7b600
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cardiology and Cardiovascular Medicine
- M. Zhou
- Taiyong Li
- Eduardo José da S. Luz
- Guillermo Cámara Chávez
- David Menotti
- William Robson Schwartz
In Cognitive Neuroscience
- M. Zhou
- Taiyong Li
- Eduardo José da S. Luz
- Guillermo Cámara Chávez
- David Menotti
- William Robson Schwartz
In Pulmonary and Respiratory Medicine
- M. Zhou
- Eduardo José da S. Luz
- Taiyong Li
- Guillermo Cámara Chávez
- David Menotti
- William Robson Schwartz
Citations in the corpus
- ECG-based heartbeat classification for arrhythmia detection: A survey (2016, methodology): “According to Yu and Chen [101], models constructed with PNN are computationally more robust and efficient than the traditional MLP.”
- ECG Classification Using Wavelet Packet Entropy and Random Forests (2016, methodology): “used PNN to build classifiers on the combined features of RR-interval and the features by Wavelet [10] and ICA [5,6], respectively.”
- Optimization of ECG Classification by Means of Feature Selection (2011, unknown): “, variances [14], [36], have been proposed.”
- Enhanced probabilistic neural network with local decision circles: A robust classifier (2010, unknown): “data analysis [58,88–90,96],power engineering [28,57,”