Results 31 to 40 of about 1,557,577 (150)
Multivariate improved weighted multi-scale permutation entropy and its application on EEG data [PDF]
, 2017 This paper introduces an entropy based method that measures complexity in non-stationary multivariate signals. This method, called Mutivariate Improved Weighted Multiscale Permutation Entropy (mvIWMPE), has two main advantages: (i) it shows lower ...
N. Jrad +15 more
core +2 more sources
Refined Composite Multivariate Generalized Multiscale Fuzzy Entropy: A Tool for Complexity Analysis of Multichannel Signals [PDF]
, 2017 Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the
Azami, Hamed, Escudero, Javier; id_orcid
core +1 more source
A noise-robust Multivariate Multiscale Permutation Entropy for two-phase flow characterisation [PDF]
, 2022 Using a graph-based approach, we propose a multiscale permutation entropy to explore the complexity of multivariate time series over multiple time scales.
Fabila-Carrasco, John Stewart +2 more
core +1 more source
, 2016 Multiscale entropy (MSE) is an appealing tool to characterize the complexity of time series over multiple temporal scales. Recent developments in the field have tried to extend the MSE technique in different ways. Building on these trends, we propose the
Azami, Hamed, Escudero, Javier
core +2 more sources
, 2017 Please see the updated Matlab codes for "Refined Composite Multiscale Dispersion Entropy and its Application to Biomedical Signals" at https://doi.org/10.7488/ds/1982 . Multiscale entropy (MSE) is a widely-used tool for the analysis of biomedical signals.
Azami, Hamed, Escudero, Javier
core +1 more source
, 2021 Refined composite multivariate multiscale fractional fuzzy entropy (RCmvMFFE), which aims to sensitively discriminate different short noisy multichannel financial data, is proposed as a new measure to quantify the complexity dynamics of multichannel time
Wei Zhang, Zhiyong Wu, Huiqin Chu
core +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley +1 more source
Multivariate generalized multiscale entropy analysis [PDF]
, 2016 Multiscale entropy (MSE) was introduced in the 2000s to quantify systems’ complexity. MSE relies on (i) a coarse-graining procedure to derive a set of time series representing the system dynamics on different time scales; (ii) the computation of the ...
A. Humeau-Heurtier +2 more
core +1 more source
An Integrated NLP‐ML Framework for Property Prediction and Design of Steels
Advanced Science, EarlyView.This study presents a data‐driven framework that uses language‐processing techniques to interpret steel processing descriptions and machine‐learning models to predict mechanical properties. By organising complex process histories into meaningful groups and enabling rapid property forecasts, the work supports faster, more informed steel design through ...
Kiran Devraju +5 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source