Results 61 to 70 of about 793 (178)

A Multivariate Method for Dynamic System Analysis: Multivariate Detrended Fluctuation Analysis Using Generalized Variance

Topics in Cognitive Science, Volume 18, Issue 3, July 2026.
Abstract Fractal fluctuations are a core concept for inquiries into human behavior and cognition from a dynamic systems perspective. Here, we present a generalized variance method for multivariate detrended fluctuation analysis (mvDFA). The advantage of this extension is that it can be applied to multivariate time series and considers intercorrelation ...
Sebastian Wallot, Julien Patrick Irmer, Monika Tschense, Nikita Kuznetsov, Andreas Højlund, Martin Dietz   +5 more
wiley   +1 more source

Quantification of the effects of uncertainties in turbulent flows through generalized Polynomial Chaos

Journal of Physics: Conference Series, 2011
Statistical methodologies based on surrogate-models have proved to be an efficient approach to quantify the physical properties of turbulent flows. The underlying idea is to parametrize the space of possible solutions via a computationally inexpensive approximation model, which is then used to generate samples for the statistical tool at hand.
M., Meldi, Lucor, Didier, P., Sagaut
openaire   +2 more sources

Generalized polynomial chaos paradigms to model uncertainty in wireless links [PDF]

2017 11th European Conference on Antennas and Propagation (EUCAP), 2017
A stochastic framework is proposed to evaluate the effect of random effects on the overall performance of wireless links. A generalized polynomial chaos expansion is leveraged to relate the uncertainties in antenna geometry, orientation and position to the figures of merit characterizing the link.
Rossi, Marco, Vande Ginste, Dries, Rogier, Hendrik   +2 more
openaire   +2 more sources

Computational uncertainty quantification for random non-autonomous second order linear differential equations via adapted gPC: a comparative case study with random Fröbenius method and Monte Carlo simulation

Open Mathematics, 2018
This paper presents a methodology to quantify computationally the uncertainty in a class of differential equations often met in Mathematical Physics, namely random non-autonomous second-order linear differential equations, via adaptive generalized ...
Calatayud Julia, Cortés Juan Carlos, Jornet Marc   +2 more
doaj   +1 more source

Volcanic Forcing Amplifies Extreme Wet‐to‐Dry in Pre‐Flood South China Driven by Internal Variability

Geophysical Research Letters, Volume 53, Issue 11, 16 June 2026.
Abstract Dry‐wet whiplash events profoundly impact society and the environment, yet their attribution remain poorly understood. This study reveals that the unprecedented interannual wet‐to‐dry transition (return period: 979.2 years) in South China's 1962–1963 pre‐flood season is co‐driven by internal variability and volcanic forcing.
Qi Wen, Yan Li, Mengying Du, Jiahao Li, Zhilan Wang, Xiaodan Guan   +5 more
wiley   +1 more source

Stable Neural Signal Recording Processed by Memristor‐Based Reservoir Computing System

Advanced Intelligent Systems, Volume 8, Issue 6, June 2026.
This work introduces a memristor‐based reservoir computing (RC) system for real‐time, energy‐efficient processing of neural signals in brain‐machine interface (BMI). Combined with flexible mesh neural probes with tissue‐like flexibility and subcellular‐scale features that enable consistent, long‐term tracking of single‐cell neural activities, the ...
Soohyeon Kim, Yuting Wu, Finn Moore, Mingtao Hu, Xiaoyu Zhang, Sangmin Yoo, Eric Yeu‐Jer Lee, Hao Shen, Yichun He, Jia Liu, Wei D. Lu   +10 more
wiley   +1 more source

Exact Solutions and Nonlinear Dynamical Behavior in a Navier‐Stokes‐Type Model for Elastic Cylindrical Vessels: An Analytical and Computational Approach

Engineering Reports, Volume 8, Issue 6, June 2026.
This study investigates a nonlinear Navier‐Stokes‐type model for elastic cylindrical vessels. Exact solutions are derived via the Bäcklund transformation and the ϕ6$$ {\phi}^6 $$‐expansion method, and dynamical behaviors are analyzed using bifurcation and chaos tools, revealing diverse wave structures and parameter‐dependent propagation characteristics.
Sheikh Zain Majid, Fatma Nur Kaya Sağlam, Mohammad Safi Ullah   +2 more
wiley   +1 more source

SENSITIVITY ANALYSIS OF IMAGE CLASSIFICATION MODELS USING GENERALIZED POLYNOMIAL CHAOS

Proceedings of the 6th International Conference on Uncertainty Quantification in Computational Sciences and Engineering (UNCECOMP)
Integrating advanced communication protocols in production has accelerated the adoption of data-driven predictive quality methods, notably machine learning (ML) models. However, ML models in image classification often face significant uncertainties arising from model, data, and domain shifts.
Lukas Bahr, Lucas Poßner, Konstantin Weise, Stephan Matzka, Sophie Gröger, Rüdiger Daub   +5 more
openaire   +3 more sources

Generative modeling with low-rank Wasserstein polynomial chaos expansions

, 2022
A new Wasserstein multi-element polynomial chaos expansion (WPCE) is proposed, which is inspired by recent advances in computational optimal transport for estimating Wasserstein distances. The developed method combines unsupervised learning with the explicit functional representation of a random vector $Y$.
Gruhlke, Robert, Eigel, Martin
openaire   +2 more sources

Influence of Head Tissue Conductivity Uncertainties on EEG Dipole Reconstruction

Frontiers in Neuroscience, 2019
Reliable EEG source analysis depends on sufficiently detailed and accurate head models. In this study, we investigate how uncertainties inherent to the experimentally determined conductivity values of the different conductive compartments influence the ...
Johannes Vorwerk, Johannes Vorwerk, Johannes Vorwerk, Ümit Aydin, Ümit Aydin, Carsten H. Wolters, Carsten H. Wolters, Christopher R. Butson, Christopher R. Butson, Christopher R. Butson   +9 more
doaj   +1 more source