Results 51 to 60 of about 19,312,029 (301)

Nonlinear Methods Most Applied to Heart-Rate Time Series: A Review

Entropy, 2020
The heart-rate dynamics are one of the most analyzed physiological interactions. Many mathematical methods were proposed to evaluate heart-rate variability.
Teresa Henriques, Maria Ribeiro, Andreia Teixeira, Luísa Castro, Luís Antunes, Cristina Costa-Santos   +5 more
doaj   +1 more source

Utility of the APE2 Score as a Diagnostic Tool for Autoimmune Encephalitis

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To retrospectively evaluate the diagnostic performance of the Antibody Prevalence in Epilepsy and Encephalopathy (APE2) score relative to clinician‐adjudicated autoimmune encephalitis (AE) and the Graus criteria in a tertiary neuroimmunology referral cohort, including antibody‐negative AE.
Bijoya Basu, Sophia F. Damman, Samhitha M. Rai, Hesham Abboud   +3 more
wiley   +1 more source

A New Hybrid Methodology for Nonlinear Time Series Forecasting

Modelling and Simulation in Engineering, 2011
Artificial neural networks (ANNs) are flexible computing frameworks and universal approximators that can be applied to a wide range of forecasting problems with a high degree of accuracy.
Mehdi Khashei, Mehdi Bijari
doaj   +1 more source

An Exponential Autoregressive Time Series Model for Complex Data

Mathematics, 2023
In this paper, an exponential autoregressive model for complex time series data is presented. As for estimating the parameters of this nonlinear model, a three-step procedure based on quantile methods is proposed. This quantile-based estimation technique
Gholamreza Hesamian, Faezeh Torkian, Arne Johannssen, Nataliya Chukhrova   +3 more
doaj   +1 more source

Automatic Lesion Morphometrics Reliably Predict Sensorimotor Recovery After Spinal Cord Injury: A Longitudinal, Multicenter Neuroimaging Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate automatic magnetic resonance imaging (MRI)‐derived lesion morphometrics against manual measurements and their prognostic value for characterizing distinct acute to chronic neurological recovery trajectories after spinal cord injury (SCI). Methods We studied a retrospective, multicenter cohort of cervical and thoracolumbar
Dario Pfyffer, Jan Valošek, Lynn Farner, Enamundram Naga Karthik, Gergely David, Norbert Weidner, Rainer Abel, Doris Maier, Armin Curt, Margret Hund‐Georgiadis, Mirko Aach, Michael Baumberger, Julien Cohen‐Adad, Patrick Freund, the Nogo Inhibition in Spinal Cord Injury Study Group, Rainer Abel, Kerstin Rehahn, Mirko Aach, Klaus Röhl, Norbert Weidner, Marion Saur, Nikolaus Weiskopf, Doris Maier, Andreas Badke, Margret Hund‐Georgiadis, Michael Baumberger, Armin Curt, Jesus Benito‐Penalva, Jiri Kriz   +28 more
wiley   +1 more source

Four‐Year Cognitive Outcomes in Multiple Sclerosis: Associations With Lesion Myelin Integrity

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objectives Cognitive impairment is prevalent in patients with multiple sclerosis (MS) but whether lesion myelin integrity influences future cognitive outcomes remains unclear. We investigated the relationship between baseline lesion myelin water fraction (MWF) and cognitive performance 4 years later.
Iliana Pliska‐Bloch, Hannah Schwartz, Kimberly H. Markowitz, Abhishek Jaywant, Christopher D. Hildenbrand, Jai Perumal, Ulrike W. Kaunzner, Thanh D. Nguyen, Sandra Hurtado Rúa, Susan A. Gauthier   +9 more
wiley   +1 more source

Recurrence Quantitative Analysis of Wavelet-Based Surrogate Data for Nonlinearity Testing in Heart Rate Variability

Frontiers in Physiology, 2022
Exploring the presence of nonlinearity through surrogate data testing provides insights into the nature of physical and biological systems like those obtained from heart rate variability (HRV). Short-term HRV time series are of great clinical interest to
Martín Calderón-Juárez, Martín Calderón-Juárez, Gertrudis Hortensia González Gómez, Juan C. Echeverría, Héctor Pérez-Grovas, Eduardo Quintanar, Claudia Lerma   +6 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, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

The Taylor Property in Bilinear Models

Revstat Statistical Journal, 2015
The aim of this paper is to discuss the presence of the Taylor property in the class of simple bilinear models. Considering strictly and weakly stationary models, we deduce autocorrelations of the process and of its square and analyze the presence of ...
E. Gonçalves , C.M. Martins , N. Mendes-Lopes   +2 more
doaj   +1 more source

A Numerical–Experimental Approach for Multi‐Matrix Fiber‐Reinforced Plastics Characterization Using Finite Element Model Updating

Advanced Engineering Materials, EarlyView.
A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora, Tales V. Lisbôa, Axel Spickenheuer, Rogério J. Marczak, Jakson M. Vassoler   +4 more
wiley   +1 more source