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Numerical simulation of viscoelastic flows is challenging because of the hyperbolic nature of viscoelastic constitutive equations. Despite their superior accuracy and efficiency, pseudo-spectral methods require the introduction of…

Fluid Dynamics · Physics 2020-10-20 Lu Zhu , Li Xi

In this study, we focus on the numerical solution method for the optimal control problem with equilibrium constraints (OCPEC).It is extremely challenging to solve OCPEC owing to the absence of constraint regularity and strictly feasible…

Optimization and Control · Mathematics 2024-05-28 Kangyu Lin , Toshiyuki Ohtsuka

In this paper, we propose a horizontal type method of lines numerical scheme for the unsteady Euler-Bernoulli beam equation. The problem is initially reformulated as a first order system of initial value problems and a suitable one-step…

Numerical Analysis · Mathematics 2025-06-05 Onur Baysal , Maria Aquilina

This paper extends the high-order entropy stable (ES) adaptive moving mesh finite difference schemes developed in [14] to the two- and three-dimensional (multi-component) compressible Euler equations with the stiffened equation of state.…

Numerical Analysis · Mathematics 2022-08-10 Shangting Li , Junming Duan , Huazhong Tang

Many new possibilities to observe and use novel physical effects are discovered at so called exceptional points (EPs). This is done by using parity-time (PT) -symmetric non-Hermitian systems and balancing gains and losses. When combined…

Applied Physics · Physics 2023-03-06 Jianlan Xie , Shaohua Dong , Bei Yan , Yuchen Peng , Jianjun Liu , Chengwei Qiu , Shuangchun Wen

Equilibrium Propagation (EP) is a learning algorithm that bridges Machine Learning and Neuroscience, by computing gradients closely matching those of Backpropagation Through Time (BPTT), but with a learning rule local in space. Given an…

Neural and Evolutionary Computing · Computer Science 2020-05-11 Maxence Ernoult , Julie Grollier , Damien Querlioz , Yoshua Bengio , Benjamin Scellier

There are recent shifts in demand for design controllers from simplified to complex model-based. Although simplification approaches are successful in many areas of engineering control systems, high-fidelity simulation-based control design,…

Systems and Control · Electrical Eng. & Systems 2024-02-15 Jongrae Kim

The high-order accurate continuous Galerkin finite element method offers attractive computational efficiency for computational fluid dynamics. A challenge is however spurious oscillations which result for convection dominated flows over…

Numerical Analysis · Mathematics 2023-11-10 Arnaud G. Malan , Jan Nordstrom

Estimating the stability boundary is a fundamental and challenging problem in transient stability studies. It is known that a proper level set of a Lyapunov function or an energy function can provide an inner approximation of the stability…

Systems and Control · Electrical Eng. & Systems 2021-10-01 Peng Yang , Feng Liu , Wei Wei , Zhaojian Wang

This work presents the design of nonlinear stabilization techniques for the finite element discretization of Euler equations in both steady and transient form. Implicit time integration is used in the case of the transient form. A…

Numerical Analysis · Mathematics 2020-08-26 Santiago Badia , Jesús Bonilla , Sibusiso Mabuza , John N. Shadid

An algorithm for detecting unstable periodic orbits in chaotic systems [Phys. Rev. E, 60 (1999), pp. 6172-6175] which combines the set of stabilising transformations proposed by Schmelcher and Diakonos [Phys. Rev. Lett., 78 (1997), pp.…

Chaotic Dynamics · Physics 2007-06-14 Jonathan J. Crofts

This paper introduces a computationally efficient method that converges globally to B-stationary points of mathematical programs with equilibrium constraints (MPECs). B-stationarity is necessary for optimality and means that no feasible…

Optimization and Control · Mathematics 2026-03-13 Armin Nurkanović , Sven Leyffer

Fast power system state estimation (SE) solution is of paramount importance for achieving real-time decision making in power grid operations. Semidefinite programming (SDP) reformulation has been shown effective to obtain the global optimum…

Signal Processing · Electrical Eng. & Systems 2019-06-20 Yu Lan , Hao Zhu , Xiaohong Guan

In this paper, we propose a dynamical systems perspective of the Expectation-Maximization (EM) algorithm. More precisely, we can analyze the EM algorithm as a nonlinear state-space dynamical system. The EM algorithm is widely adopted for…

Optimization and Control · Mathematics 2018-10-05 Orlando Romero , Sarthak Chatterjee , Sérgio Pequito

Many entropy-conservative and entropy-stable (summarized as entropy-preserving) methods for hyperbolic conservation laws rely on Tadmor's theory for two-point entropy-preserving numerical fluxes and its higher-order extension via flux…

Numerical Analysis · Mathematics 2026-03-26 Marco Artiano , Hendrik Ranocha

Equilibrium propagation (EP) is an alternative to backpropagation (BP) that allows the training of deep neural networks with local learning rules. It thus provides a compelling framework for training neuromorphic systems and understanding…

Machine Learning · Computer Science 2022-09-02 Axel Laborieux , Friedemann Zenke

The compact Variation Evolving Method (VEM) that originates from the continuous-time dynamics stability theory seeks the optimal solutions with variation evolution principle. It is further developed to be more flexible in solving the…

Systems and Control · Computer Science 2017-12-29 Sheng Zhang , En-Mi Yong , Wei-Qi Qian

Entropy notions for $\varepsilon$-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which…

Optimization and Control · Mathematics 2022-09-13 Michelle S. Chong

A new method for the optimal solutions is proposed. Originating from the continuous-time dynamics stability theory in the control field, the optimal solution is anticipated to be obtained in an asymptotically evolving way. By introducing a…

Systems and Control · Computer Science 2017-04-11 Sheng Zhang , En-Mi Yong , Wei-Qi Qian , Kai-Feng He

Equilibrium Propagation (EP) is a supervised learning algorithm that trains network parameters using local neuronal activity. This is in stark contrast to backpropagation, where updating the parameters of the network requires significant…

Machine Learning · Computer Science 2025-04-01 Jonathan Peters , Philippe Talatchian
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