Comprehensive review on detection and classification of power quality disturbances in utility grid with renewable energy penetration

GS Chawda, AG Shaik, M Shaik, S Padmanaban… - IEEE …, 2020 - ieeexplore.ieee.org
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 …

Fault detection, classification and location for transmission lines and distribution systems: a review on the methods

K Chen, C Huang, J He - High voltage, 2016 - Wiley Online Library
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 …

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 …

Seismic detection of the martian core

SC Stähler, A Khan, WB Banerdt, P Lognonné… - Science, 2021 - science.org
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 …

A hybrid algorithm for recognition of power quality disturbances

R Kaushik, OP Mahela, PK Bhatt, B Khan… - IEEE …, 2020 - ieeexplore.ieee.org
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 …

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 …

Deep convolutional neural network model for automated diagnosis of schizophrenia using EEG signals

SL Oh, J Vicnesh, EJ Ciaccio, R Yuvaraj, UR Acharya - Applied Sciences, 2019 - mdpi.com
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 …

[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 …

Brain-to-brain synchrony during naturalistic social interactions

S Kinreich, A Djalovski, L Kraus, Y Louzoun… - Scientific reports, 2017 - nature.com
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 …

Fusion of multivariate EEG signals for schizophrenia detection using CNN and machine learning techniques

F Hassan, SF Hussain, SM Qaisar - Information Fusion, 2023 - Elsevier
Schizophrenia is a severe mental disorder that has adverse effects on the behavior of an
individual such as disorganized speech and delusions. Electroencephalography (EEG) …