Results 221 to 230 of about 4,055 (251)

Emotion recognition from EEG signals by using multivariate empirical mode decomposition

Pattern Analysis and Applications, 2016
This is the artifact for the paper titled "POKER: Permutation-based SIMD Execution of Intensive Tree Search by Path Encoding" accepted at CGO 2018. This artifact helps reproduce the results presented in Figures 7 - 9 and Tables 2 - 3 in Section 4. For more information on how to use it, please refer to our paper and the README.txt file in this package ...
Ahmet Mert, Aydin Akan
openaire   +1 more source

Pulsar signal de-noising method based on multivariate empirical mode decomposition

2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2015
In this paper, the de-noising method based on multivariate empirical mode decomposition (MEMD) is creatively proposed to put use to pulsar signal, filling the void that the previous methods based on the wavelet analysis have the limitations of choosing the basic functions, and the EMD algorithm's bounded that it can't process multiple signals jointly ...
Jing Jin 0003, Xiuxiu Ma, Xiaoyu Li, Yi Shen 0001, Liangwei Huang, Liang He   +5 more
openaire   +1 more source

Learning multivariate empirical mode decomposition for spectral motion editing

SIGGRAPH Asia 2023 Technical Communications, 2023
Ran Dong, Soichiro Ikuno, Xi Yang 0017
openaire   +1 more source

Preterm birth prediction from electrohysterogram using multivariate empirical mode decomposition

Medical & Biological Engineering & Computing
Electrohysterogram (EHG) is an electrophysiological signal describing uterine contractions that can be non-invasively measured on maternal abdominal surface. This signal contains vital physiological and pathological information for assessing delivery abnormalities, such as preterm birth.
Jiawen Cui, Xu Zhang 0002, Xinhui Li, Xuanyu Luo, Xiang Chen 0004, Zongzhi Yin   +5 more
openaire   +2 more sources

MULTIVARIATE EXTENSIONS OF EMPIRICAL MODE DECOMPOSITION

2014
Naveed ur Rehman, David Looney, Alireza Ahrabian, Cheolsoo Park, Danilo P. Mandic   +4 more
openaire   +1 more source

Improved uniform phase empirical mode decomposition and its application in machinery fault diagnosis

Measurement: Journal of the International Measurement Confederation, 2021
Jinde Zheng, Jinyu Tong, Wanming Ying
exaly  

Hyperspectral image classification with multivariate empirical mode decomposition-based features

2014 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings, 2014
Zhi He, Miao Zhang 0001, Yi Shen 0001, Qiang Wang 0001, Yan Wang 0047, Renlong Yu   +5 more
openaire   +1 more source

Estimation of Intrinsic Connectivity Networks by Multivariate Empirical Mode Decomposition

2018
Functional brain mapping is based on electrical andhaemodynamic changes occured in the brain. Blood oxeygenated level dependency(BOLD) signal can be non-invasively collected through the use of functionalMagnetic Resonance Imaging (fMRI). Brain functional activity can also beobserved in the absence of a given task.
openaire   +1 more source

Water quality event detection based on Multivariate empirical mode decomposition

2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC), 2014
Zheling Yang, Yang Liu, Dibo Hou, Tianheng Feng, Yuan Wei, Jian Zhang, Pingjie Huang, Guangxin Zhang   +7 more
openaire   +1 more source

Power System Dominant Oscillation Mode Analysis Based on Multivariate Empirical Mode Decomposition

2023 3rd International Conference on Energy Engineering and Power Systems (EEPS), 2023
Yue Zuo, Xingcai Wang, Bo Zhang
openaire   +1 more source