Results 91 to 100 of about 2,284 (152)

Symplectomorphic registration with phase space regularization by entropy spectrum pathways. [PDF]

Magn Reson Med, 2019
Galinsky VL, Frank LR.
europepmc   +1 more source

Mock Modularity at Work, or Black Holes in a Forest. [PDF]

Entropy (Basel)
Alexandrov S.
europepmc   +1 more source

Harnessing population diversity: in search of tools of the trade. [PDF]

Gigascience
Bzdok D, Wolf G, Kopal J.
europepmc   +1 more source

Application of Symplectic Geometry Mode Decomposition Based on Gaussian Process Space Angle in DOA Estimation

IEEE Transactions on Instrumentation and Measurement, 2023
In the presence of noise interference, direction of arrival (DOA) estimation becomes challenging. Particularly, when radar signals are entirely submerged in noise, the spatial information within the signals becomes obscured, thereby affecting the precision of DOA estimation.
Zhaolin Zhang, Yinan Zhao, Wugang Meng, Yingchun Li, Ming Jin   +4 more
semanticscholar   +4 more sources

Output-Only Structural System Identification Based on Symplectic Geometry Mode Decomposition

Volume 1: Acoustics, Vibration, and Phononics, 2021
Abstract In this paper, a novel output-only structural system identification method is proposed based on the decomposition of the response signal by applying newly developed symplectic geometry mode decomposition (SGMD). The SGMD can decompose the output signal into a limited of single component signals which are also called symplectic ...
Pengming Zhan, Xianrong Qin, Qing Zhang, Yuantao Sun   +3 more
semanticscholar   +3 more sources

Cycle kurtosis entropy guided symplectic geometry mode decomposition for detecting faults in rotating machinery

ISA Transactions, 2023
Strong noise interference or compound fault coupling phenomenon may lead to the failure of fault diagnosis technology. This paper focuses on weak feature extraction and compound faults detection for rotating machinery fault diagnosis and proposes adaptive symplectic geometric mode decomposition (SGMD) using cycle kurtosis entropy.
Jianchun Guo, Zetian Si, Jiawei Xiang
semanticscholar   +4 more sources

Symplectic geometry mode decomposition and its application to rotating machinery compound fault diagnosis

Mechanical Systems and Signal Processing, 2018
Abstract Various existed time-series decomposition methods, including wavelet transform, ensemble empirical mode decomposition (EEMD), local characteristic-scale decomposition (LCD), singular spectrum analysis (SSA), etc., have some defects for nonlinear system signal analysis.
Haiyang Pan, Yu Yang, Xin Li, Jinde Zheng, Junsheng Cheng   +4 more
semanticscholar   +3 more sources

Structural Modal Parameters Identification Under Ambient Excitation Using Optimized Symplectic Geometry Mode Decomposition

International Journal of Structural Stability and Dynamics, 2023
In the process of structural modal parameters identification under environmental excitation, the employed measured dynamic response signal is usually non-stationary and contains noise. As a novel signal analyzed method, symplectic geometry mode decomposition (SGMD) has been proven to be effective for dealing with non-stationary and noisy signals ...
Feng Hu, Lunhai Zhi, Kang Zhou, Shouji Li, Zhixiang Hu   +4 more
semanticscholar   +3 more sources

A Fault Diagnosis Method Based on Optimized SVDD And Multi-Symplectic Geometry Mode Decomposition for Rolling Bearings

2023 23rd International Conference on Control, Automation and Systems (ICCAS), 2023
The machine learning-based intelligent fault diagnosis method has the merits of fast response speed and automation, but requires many fault samples which are difficult to obtain.
Jianqun Zhang, Qing Zhang, Wenzong Feng, Yuantao Sun   +3 more
semanticscholar   +3 more sources