Results 121 to 130 of about 93,147 (298)

Invariant Measure and Universality of the 2D Yang–Mills Langevin Dynamic

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT We prove that the Yang–Mills (YM) measure for the trivial principal bundle over the two‐dimensional torus, with any connected, compact structure group, is invariant for the associated renormalised Langevin dynamic. Our argument relies on a combination of regularity structures, lattice gauge‐fixing and Bourgain's method for invariant measures ...
Ilya Chevyrev, Hao Shen
wiley   +1 more source

Modal Parameter Identification of the Improved Random Decrement Technique-Stochastic Subspace Identification Method Under Non-Stationary Excitation

Applied Sciences
Commonly used methods for identifying modal parameters under environmental excitations assume that the unknown environmental input is a stationary white noise sequence.
Jinzhi Wu, Jie Hu, Ming Ma, Chengfei Zhang, Zenan Ma, Chunjuan Zhou, Guojun Sun   +6 more
doaj   +1 more source

Fast estimation methods for time series models in state-space form [PDF]

We propose two fast, stable and consistent methods to estimate time series models expressed in their equivalent state-space form. They are useful both, to obtain adequate initial conditions for a maximum-likelihood iteration, or to provide final ...
Alfredo García Hiernaux, José Casals Carro, Miguel Jerez   +2 more
core  

The Benjamin–Ono Equation in the Zero‐Dispersion Limit for Rational Initial Data: Generation of Dispersive Shock Waves

Communications on Pure and Applied Mathematics, EarlyView.
ABSTRACT The leading‐order asymptotic behavior of the solution of the Cauchy initial‐value problem for the Benjamin–Ono equation in L2(R)$L^2(\mathbb {R})$ is obtained explicitly for generic rational initial data u0$u_0$. An explicit asymptotic wave profile uZD(t,x;ε)$u^\mathrm{ZD}(t,x;\epsilon)$ is given, in terms of the branches of the multivalued ...
Elliot Blackstone, Louise Gassot, Patrick Gérard, Peter D. Miller   +3 more
wiley   +1 more source

LQ decomposition based subspace identification under deterministic type disturbance

Systems Science & Control Engineering, 2017
To overcome the influence from deterministic type load disturbance with unknown dynamics, a bias-eliminated subspace identification method is proposed for consistent estimation.
Shengnan Zhang, Tao Liu, Jie Hou, Xiongwei Ni   +3 more
doaj   +1 more source

Meta-models of repeated dissipative joints for damping design phase [PDF]

, 2014
Developing tools to predict dissipation in mechanical assemblies starting from the design process is a subject of increasing interest. Design phases imply numerous computations resulting from the use of families of models with varying properties ...
BALMES, Etienne, HAMMAMI, Chaima
core   +3 more sources

Random finite element analysis on ground subsidence caused by tunnel excavation in karst regions with spatial variable soil

Deep Underground Science and Engineering, EarlyView.
This study investigates ground subsidence during tunnel excavation in karst areas, highlighting the combined effects of karst cave proximity, cave size, and soil spatial variability. Findings suggest that shorter cave distances and larger cave sizes increase subsidence variability, and a modified Peck formula is proposed for more accurate subsidence ...
Zhenghong Su, Yong Fu, Miaomiao Sun, Kailin Ding, Ying Zhao   +4 more
wiley   +1 more source

Thalamic connectivity mirrors spatial maps of network dysfunction in nonlesional focal epilepsy

Epilepsia, EarlyView.
Abstract Objective Focal epilepsy is increasingly conceptualized as a network disorder, yet the extent to which network dysfunction reflects a shared phenotype remains unknown. Spatially conserved patterns of network dysfunction may implicate a centralized mechanism underlying widespread impairment.
Joline M. Fan, Ehsan Tadayon, Kiwamu Kudo, Kamalini G. Ranasinghe, Anne M. Findlay, Robert C. Knowlton, Vikram R. Rao, Srikantan S. Nagarajan   +7 more
wiley   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source

Longitudinal Tire Force Estimation Method for 4WIDEV Based on Data-Driven Modified Recursive Subspace Identification Algorithm

Algorithms
For the longitudinal tire force estimation problem of four-wheel independent drive electric vehicles (4WIDEVs), traditional model-based observers have limitations such as high modeling complexity and strong parameter sensitivity, while pure data-driven ...
Xiaoyu Wang, Te Chen, Jiankang Lu
doaj   +1 more source