Yu-Te Wang

Cognitive Neuroscience · 2014–2017

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 37 citations into it; #5,431 of 10,852 by trust here, #8,619 by citations
• Cellular and Molecular Neuroscience — 23 citations into it; #1,392 of 2,998 by trust here, #2,821 by citations
• Electrical and Electronic Engineering — 11 citations into it
• Signal Processing — 7 citations into it

Whom Yu-Te Wang trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Xiaorong Gao
2. Guangyu Bin
3. Shangkai Gao
4. Masaki Nakanishi
5. Jonathan R. Wolpaw
6. François-Benoît Vialatte
7. Changshui Zhang
8. Ola Friman
9. Bo Hong
10. Pradeep Shenoy

Who trusts Yu-Te Wang overall

1. Masaki Nakanishi
2. Xiaogang Chen
3. Tzyy-Ping Jung

Papers from Yu-Te Wang's perspective

Ordered by how strongly the researchers Yu-Te Wang trusts endorse each paper. Same corpus, a different order for every researcher.

1. Brain-computer interfaces for communication and control. (Clinical Neurophysiology)
2. Multiple Channel Detection of Steady-State Visual Evoked Potentials for Brain-Computer Interfaces (IEEE Transactions on Biomedical Engineering)
3. An online multi-channel SSVEP-based brain–computer interface using a canonical correlation analysis method (Journal of Neural Engineering)
4. Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis (NeuroImage)
5. A high-speed BCI based on code modulation VEP (Journal of Neural Engineering)
6. Visual and Auditory Brain–Computer Interfaces (IEEE Transactions on Biomedical Engineering)
7. A High-Speed Brain Speller using steady-State Visual evoked potentials (International Journal of Neural Systems)
8. The Hybrid BCI (Frontiers in Neuroscience)
9. Frequency Recognition Based on Canonical Correlation Analysis for SSVEP-Based BCIs (IEEE Transactions on Biomedical Engineering)
10. Imaging human EEG dynamics using independent component analysis. (Neuroscience and Biobehavioral Reviews)

Their papers

• Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis (2017) — 696 citations
• A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials (2015) — 352 citations
• A High-Speed Brain Speller using steady-State Visual evoked potentials (2014) — 346 citations