Results 71 to 80 of about 1,586 (236)
IET Signal Processing, Volume 2026, Issue 1, 2026.The burst‐like and high‐amplitude characteristics of impulsive noise, which markedly differ from those of Gaussian noise, render methods based on the Gaussian assumption unable to accurately characterize signals under impulsive noise. Moreover, when dealing with multicomponent signal, existing impulsive noise suppression methods inevitably introduce ...
Weiwei Shang +3 more
wiley +1 more source
IET Science, Measurement &Technology, Volume 20, Issue 1, January/December 2026.This study uses chaotic synchronisation and fractal analysis of acoustic partial discharge signals in 25‐kV cable joints. Extracted 3D error trace features combined with a neural network enable accurate, noise‐robust defect recognition, effectively distinguishing different cable joint defect types with high reliability and ease of implementation ...
Feng‐Chang Gu, Sen‐Fu Chan
wiley +1 more source
Synchrosqueezing Transform in Biomedical Applications: A mini review
, 2020 2020 Medical Technologies Congress, TIPTEKNO 2020 -- 19 November 2020 through 20 November 2020 -- 166140Time-frequency representation (TFR) provides a good analysis for periodic signals; however, they are insufficient for nonstationary signals.
Akan A. +7 more
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AI‐Based Approaches for Analyzing EEG Signals to Identify Epileptic Seizures: A Survey
Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.Electroencephalography (EEG) is a fundamental tool for monitoring brain activity and is widely used in the diagnosis and management of epilepsy. With the growing prevalence of epilepsy and the limitations of manual EEG interpretation, artificial intelligence (AI) techniques, particularly machine learning (ML) and deep learning (DL), have gained ...
Daniel Moges Tadesse +10 more
wiley +1 more source
Synchrosqueezing-based Transform and its Application in Seismic Data Analysis [PDF]
Iranian Journal of Oil & Gas Science and Technology, 2015 Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms are suitable tools for analyzing non-stationary seismic signals.
Saman Gholtashi +4 more
doaj +1 more source
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Depression is a serious mental disorder, and timely detection and treatment are crucial. Electroencephalography (EEG), as a noninvasive tool directly reflecting brain activity, is suitable for objective depression detection. However, due to difficulty in acquiring depression EEG data, public datasets suffer from limited sample sizes and insufficient ...
Huang Huang +6 more
wiley +1 more source
Drive‐by frequencies extraction by means of synchrosqueezed wavelet transform [PDF]
, 2023 Lorenzo Benedetti +3 more
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A Topological Signal Processing‐Based Time–Frequency Analysis Algorithm
Structural Control and Health Monitoring, Volume 2026, Issue 1, 2026.A topological signal processing framework is introduced to enhance the noise robustness of synchrosqueezing‐based time–frequency (TF) analysis. Designed as a postprocessing procedure applicable to any TF representation, the method produces a more energy‐concentrated and sparse TF spectrum. The approach begins with the short‐time Fourier transform (STFT)
Peng Guo +2 more
wiley +1 more source
A Novel Method of Realizing Stochastic Chaotic Secure Communication by Synchrosqueezed Wavelet Transform: The Finite-Time Case [PDF]
, 2021 Jia Hu, Bing Liu, Min Yu
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Second-order Synchrosqueezing Transform: The Wavelet Case, Comparisons and Applications
, 2018 This paper addresses the analysis of the time-frequency technique so-called the second-order synchrosqueezing transform derived from continuous wavelet transform of multicomponent AM-FM signals.
Pham, Duong-Hung, Meignen, Sylvain
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