Results 181 to 190 of about 157,192 (284)

On Challenges Using Long Short‐Term Memory Networks in Data‐Driven Inelasticity

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT We present a framework that integrates long short‐term memory (LSTM) networks into a two‐dimensional data‐driven mechanics solver. We show that the staggered, double‐minimization algorithm induces solver‐generated noise, and that an LSTM trained on noise‐free stress–strain paths fails to account for these solver artifacts.
Marius Harnisch   +3 more
wiley   +1 more source

Simultaneous Inversion for Underactuated Mechanical Systems with Servo‐Constraints

open access: yesProceedings in Applied Mathematics and Mechanics, Volume 26, Issue 2, June 2026.
ABSTRACT The dynamic inversion of underactuated mechanical systems can be formulated in the servo‐constraint framework using a set of differential‐algebraic equations (DAEs). In case of a high differentiation index, the inversion‐based feedforward control design poses significant challenges.
Tengman Wang
wiley   +1 more source

Analysis of a Mathematical Model of Marital Satisfaction

open access: yesMathematical Methods in the Applied Sciences, Volume 49, Issue 7, Page 6143-6157, 15 May 2026.
ABSTRACT A large number of marriages end in divorce. In this paper, we present a model for the emotional state of a couple based on bilinear ordinary differential equations. We study the effect of changes of each individual's self‐emotional state on the couple's state.
Benito Chen‐Charpentier   +2 more
wiley   +1 more source

Comparative Analysis of the Performances of a Nonlinear Observer and Nonlinear Kalman Filters in the Presence of Non‐Gaussian Disturbances

open access: yesInternational Journal of Robust and Nonlinear Control, Volume 36, Issue 7, Page 3896-3913, 10 May 2026.
ABSTRACT This paper focuses on state estimation for a fairly general class of systems, involving nonlinear functions and disturbances in both the process dynamics and output equations. A nonlinear observer that satisfies a H∞$$ {\boldsymbol{H}}_{\boldsymbol{\infty}} $$ disturbance attenuation constraint in addition to providing asymptotic stability in ...
Hamidreza Movahedi   +2 more
wiley   +1 more source

Unveil Fundamental Graph Properties for Neural Architecture Search

open access: yesAdvanced Science, Volume 13, Issue 25, 4 May 2026.
This paper proposes NASGraph, a graph‐based framework that represents neural architectures as graphs whose structural properties determine performance. By revealing structure–performance relationships, NASGraph enables efficient neural architecture search with significantly reduced computation.
Zhenhan Huang   +4 more
wiley   +1 more source

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