Review of machine and deep learning techniques in epileptic seizure detection using physiological signals and sentiment analysis
Epilepsy is one of the significant neurological disorders affecting nearly 65 million people
worldwide. The repeated seizure is characterized as epilepsy. Different algorithms were …
worldwide. The repeated seizure is characterized as epilepsy. Different algorithms were …
New insights and best practices for the successful use of Empirical Mode Decomposition, Iterative Filtering and derived algorithms
Abstract Algorithms based on Empirical Mode Decomposition (EMD) and Iterative Filtering
(IF) are largely implemented for representing a signal as superposition of simpler well …
(IF) are largely implemented for representing a signal as superposition of simpler well …
Adaptive local iterative filtering for signal decomposition and instantaneous frequency analysis
Time–frequency analysis for non-linear and non-stationary signals is extraordinarily
challenging. To capture features in these signals, it is necessary for the analysis methods to …
challenging. To capture features in these signals, it is necessary for the analysis methods to …
Automated system for epileptic EEG detection using iterative filtering
The nonstationary characteristics present in electroencephalogram (EEG) signal require a
crucial analysis that can reveal a method for diagnosis of neurological abnormalities …
crucial analysis that can reveal a method for diagnosis of neurological abnormalities …
Magnetospheric–ionospheric–lithospheric coupling model. 1: Observations during the 5 August 2018 Bayan Earthquake
The short-term prediction of earthquakes is an essential issue connected with human life
protection and related social and economic matters. Recent papers have provided some …
protection and related social and economic matters. Recent papers have provided some …
Iterative filtering as a direct method for the decomposition of nonstationary signals
A Cicone - Numerical Algorithms, 2020 - Springer
Abstract The Iterative Filtering method is a technique developed recently for the
decomposition and analysis of nonstationary and nonlinear signals. In this work, we propose …
decomposition and analysis of nonstationary and nonlinear signals. In this work, we propose …
Numerical analysis for iterative filtering with new efficient implementations based on FFT
The development of methods able to extract hidden features from non-stationary and non-
linear signals in a fast and reliable way is of high importance in many research fields. In this …
linear signals in a fast and reliable way is of high importance in many research fields. In this …
Improving the detection of thermal bridges in buildings via on-site infrared thermography: The potentialities of innovative mathematical tools
The detection of thermal bridges in buildings is one of the key points to be taken into account
in energy saving procedures during refurbishment works. Passive infrared thermography …
in energy saving procedures during refurbishment works. Passive infrared thermography …
Medical image analysis using AM-FM models and methods
KP Constantinou, IP Constantinou… - IEEE Reviews in …, 2020 - ieeexplore.ieee.org
Medical image analysis methods require the use of effective representations for
differentiating between lesions, diseased regions, and normal structure. Amplitude …
differentiating between lesions, diseased regions, and normal structure. Amplitude …
Multivariate fast iterative filtering for the decomposition of nonstationary signals
A Cicone, E Pellegrino - IEEE Transactions on Signal …, 2022 - ieeexplore.ieee.org
In this work, we present a new technique for the decomposition of multivariate data, which
we call Multivariate Fast Iterative Filtering (MvFIF) algorithm. We study its properties, proving …
we call Multivariate Fast Iterative Filtering (MvFIF) algorithm. We study its properties, proving …