14 Papers
9 Citations
Ke Zeng is an academic researcher from McGovern Institute for Brain Research. The author has contributed to research in topics: General-purpose computing on graphics processing units & Graphics processing unit. The author has an hindex of 8, co-authored 14 publications. Previous affiliations of Ke Zeng include Beijing Normal University.
Chat about Author
Papers
Fast and Scalable Multi-Way Analysis of Massive Neural Data
TL;DR: A large-scale PARAFAC method is developed, which is supported by general-purpose computing on the graphics processing unit (GPGPU) and forms the basis of a model for the analysis of electrocochleography recordings obtained from epilepsy patients, which proves to be effective in the epilepsy state detection.
89
An EEMD-ICA Approach to Enhancing Artifact Rejection for Noisy Multivariate Neural Data
Ke Zeng,Dan Chen,Gaoxiang Ouyang,Lizhe Wang,Xianzeng Liu,Xiaoli Li +5 more
- 01 Jun 2016
TL;DR: Experimental results indicate that the proposed EEMD-ICA continuously outperforms the counterparts in terms of both normalized mean square error (NMSE) and Structure SIMilarity (SSIM) and the superiority becomes even greater with the decrease of SNR.
77
Automatic detection of absence seizures with compressive sensing EEG
TL;DR: The altered compressibility of EEG with CS can act as a good biomarker for distinguish seizure-free, per-seizure and seizure state and enables tele-monitoring of epilepsy patients using wireless body-area networks in personalized medicine.
69
Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes.
Ke Zeng,Ke Zeng,Yinghua Wang,Yinghua Wang,Gaoxiang Ouyang,Gaoxiang Ouyang,Zhijie Bian,Lei Wang,Xiaoli Li,Xiaoli Li +9 more
TL;DR: The correlation between cognitive states and network characteristics suggested that the more in deterioration of the diabetes patients' cognitive state, the less optimal the network organization become.
Characterizing dynamics of absence seizure EEG with spatial-temporal permutation entropy
TL;DR: The view that EEG has a detectable change prior to an absence seizure, and MMPE could be considered as a candidate precursor of the impending absence seizures is supported.
34