Tzyy-Ping Jung
researcher
Facts
8 properties- Instance of
- human
- Date of birth
- 1962
- Occupation
- researcher, electrical engineer
- Field of work
- electroencephalography[4]
- Official website
- sccn.ucsd.edu[8]
🏷️ Also known as
en Tzyy-Ping Jung
🔖 Identifiers · 10
- ISNI
- 0000000498236977
- ORCID iD
- 0000-0002-8377-2166
- VIAF cluster ID
- 10149485990393422527
- Library of Congress Authorities ID
- no2017060012
- GND ID
- 1290920052
- DBLP author ID
- 71/2079
- Google Knowledge Graph ID
- /g/11gmzhffmg
- Google Scholar author ID
- IWsSoAUAAAAJ
- OpenMLOL author ID
- 301094
- RILM ID
- 283406
🔗 Connections
Author of 85
A brain-computer interface based on high-frequency steady-state asymmetric visual evoked potentials,
A Brain–Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli,
A Brain-Computer Interface Based on Multifocal SSVEPs Detected by Inter-Task-Related Component Analysis,
Accurate Mental Stress Detection Using Sequential Backward Selection and Adaptive Synthetic Methods,
A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials,
A data expansion technique based on training and testing sample to boost the detection of SSVEPs for brain-computer interfaces,
A dynamic stopping method for improving performance of steady-state visual evoked potential based brain-computer interfaces,
A high-speed hybrid brain-computer interface with more than 200 targets
+77 more
← Authored by 85
A brain-computer interface based on high-frequency steady-state asymmetric visual evoked potentials,
A Brain–Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli,
A Brain-Computer Interface Based on Multifocal SSVEPs Detected by Inter-Task-Related Component Analysis,
Accurate Mental Stress Detection Using Sequential Backward Selection and Adaptive Synthetic Methods,
A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials,
A data expansion technique based on training and testing sample to boost the detection of SSVEPs for brain-computer interfaces,
A dynamic stopping method for improving performance of steady-state visual evoked potential based brain-computer interfaces,
A high-speed hybrid brain-computer interface with more than 200 targets
+77 more
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