Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration
The global concern with power quality is increasing due to the penetration of renewable
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …
energy (RE) sources to cater the energy demands and meet de-carbonization targets. Power …
Fault detection, classification and location for transmission lines and distribution systems: a review on the methods
A comprehensive review on the methods used for fault detection, classification and location
in transmission lines and distribution systems is presented in this study. Though the three …
in transmission lines and distribution systems is presented in this study. Though the three …
广义S 变换与薄互层地震响应分析
高静怀 - 地球物理学报, 2003 - dzkx.org
Stockwell 等人提出的S 变换虽然与Fourier 谱能保持直接联系, 然而, 由于S
变换中的基本小波不适用于地震资料处理. 为此本文采用两个步骤对S 变换加以推广 …
变换中的基本小波不适用于地震资料处理. 为此本文采用两个步骤对S 变换加以推广 …
Seismic detection of the martian core
Clues to a planet's geologic history are contained in its interior structure, particularly its core.
We detected reflections of seismic waves from the core-mantle boundary of Mars using …
We detected reflections of seismic waves from the core-mantle boundary of Mars using …
A hybrid algorithm for recognition of power quality disturbances
An algorithm making use of hybrid features of Hilbert transform (HT) and Stockwell transform
(ST) to identify the single-stage and multiple (multi-stage) power quality disturbances …
(ST) to identify the single-stage and multiple (multi-stage) power quality disturbances …
The fast continuous wavelet transformation (fCWT) for real-time, high-quality, noise-resistant time–frequency analysis
LPA Arts, EL van den Broek - Nature Computational Science, 2022 - nature.com
The spectral analysis of signals is currently either dominated by the speed–accuracy trade-
off or ignores a signal's often non-stationary character. Here we introduce an open-source …
off or ignores a signal's often non-stationary character. Here we introduce an open-source …
Deep convolutional neural network model for automated diagnosis of schizophrenia using EEG signals
A computerized detection system for the diagnosis of Schizophrenia (SZ) using a
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
convolutional neural system is described in this study. Schizophrenia is an anomaly in the …
[图书][B] Analyzing neural time series data: theory and practice
MX Cohen - 2014 - books.google.com
A comprehensive guide to the conceptual, mathematical, and implementational aspects of
analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This …
analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings. This …
Brain-to-brain synchrony during naturalistic social interactions
The evolution of humans as a highly social species tuned the brain to the social world; yet
the mechanisms by which humans coordinate their brain response online during social …
the mechanisms by which humans coordinate their brain response online during social …
Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques
Schizophrenia is a severe mental disorder that has adverse effects on the behavior of an
individual such as disorganized speech and delusions. Electroencephalography (EEG) …
individual such as disorganized speech and delusions. Electroencephalography (EEG) …