Results 51 to 60 of about 35,745,185 (300)
The Influence of EEG References on the Analysis of Spatio-Temporal Interrelation Patterns
Frontiers in Neuroscience, 2019 The characterization of the functional network of the brain dynamics has become a prominent tool to illuminate novel aspects of brain functioning.
Wady A. Ríos-Herrera +15 more
doaj +1 more source
dynoGP: Deep Gaussian Processes for Dynamic System Identification
International Journal of Adaptive Control and Signal Processing, EarlyView.This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli +3 more
wiley +1 more source
Statistical analysis of multivariate discrete-valued time series
Journal of Multivariate Analysis, 2022 The authors provide an overview of statistical analysis for some models for multivariate discrete-valued time series. They review observation-driven models and models based on higher-order Markov chains.
Konstantinos Fokianos +3 more
openaire +5 more sources
A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys
Advanced Engineering Materials, EarlyView.High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin +14 more
wiley +1 more source
Variance changes detection in multivariate time series [PDF]
, 2004 This paper studies the detection of step changes in the variances and in the correlation structure of the components of a vector of time series. Two procedures are considered.
Peña, Daniel +3 more
core +1 more source
Entropy, 2016 Simultaneously analyzing multivariate time series provides an insight into underlying interaction mechanisms of cardiovascular system and has recently become an increasing focus of interest.
Lina Zhao +3 more
doaj +1 more source
LBP4MTS: Local Binary Pattern-Based Unsupervised Representation Learning of Multivariate Time Series
IEEE Access, 2023 Representation learning of multivariate time series is a crucial and complex task that offers valuable insights for numerous applications, including time series classification, trend analysis, and regression.
Chengyang Ye, Qiang Ma
doaj +1 more source
Advanced Functional Materials, EarlyView.An integrated pulmonary mRNA delivery platform combining novel biodegradable syringic acid‐derived ionizable lipids, design‐of‐experiments formulation optimization, and vibrating‐mesh nebulizer engineering enabled stable aerosolization and efficient lung delivery.
Neha Kaushal +21 more
wiley +1 more source
Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
wiley +1 more source
Advanced Materials, EarlyView.Anion‐exchange doping of conjugated polymers is an effective way to achieve high conductivities. Here, we report over 2000 S cm−1 electrical conductivity for doped P(g3BTTT). In addition, we show that P(g3BTTT) sustains exceptionally high doping levels without any drop in the charge mobility.
Basil Hunger +14 more
wiley +1 more source