Results 101 to 110 of about 97,564 (280)

In‐Sensor Computing by Soft Threshold Logic Gates Under Different Humidity Conditions

open access: yesAdvanced Electronic Materials, EarlyView.
Soft nanocomposite materials, based on gold cluster‐assembled thin films implanted in polydimethylsiloxane substrate, can perform reliable processing in ambient environmental conditions. Humidity influences the resistive switching and computational capabilities of the nanocomposites, that can be used as multifunctional material combining sensing ...
Giacomo Nadalini   +2 more
wiley   +1 more source

Factorization of piecewise constant matrix functions and systems of linear differential equations

open access: yes, 1999
Let G be a piecewise constant $n\times n$ matrix function which is defined on a smooth closed curve $ $ in the complex sphere and which has m jumps. We consider the problem of determining the partial indices of the factorization of the matrix function G in the space $L^p( )$.
Ehrhardt, T., Spitkovsky, I. M.
openaire   +3 more sources

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

open access: yesAdvanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source

Polynomial approximation of Poincare maps for Hamiltonian system [PDF]

open access: yes
Different methods are proposed and tested for transforming a non-linear differential system, and more particularly a Hamiltonian one, into a map without integrating the whole orbit as in the well-known Poincare return map technique.
Froeschle, Claude, Petit, Jean-Marc
core   +1 more source

Ultra-high-frequency piecewise-linear chaos using delayed feedback loops

open access: yes, 2012
We report on an ultra-high-frequency (> 1 GHz), piecewise-linear chaotic system designed from low-cost, commercially available electronic components.
Chua L. O.   +3 more
core   +1 more source

RAMS: Residual‐Based Adversarial‐Gradient Moving Sample Method for Scientific Machine Learning in Solving Partial Differential Equations

open access: yesAdvanced Intelligent Discovery, EarlyView.
We propose a residual‐based adversarial‐gradient moving sample (RAMS) method for scientific machine learning that treats samples as trainable variables and updates them to maximize the physics residual, thereby effectively concentrating samples in inadequately learned regions.
Weihang Ouyang   +4 more
wiley   +1 more source

Viscosity Solution of Mean-Variance Portfolio Selection of a Jump Markov Process with No-Shorting Constraints

open access: yesJournal of Applied Mathematics, 2016
We consider the so-called mean-variance portfolio selection problem in continuous time under the constraint that the short-selling of stocks is prohibited where all the market coefficients are random processes.
Moussa Kounta
doaj   +1 more source

Lorenz-like systems and classical dynamical equations with memory forcing: a new point of view for singling out the origin of chaos

open access: yes, 2002
A novel view for the emergence of chaos in Lorenz-like systems is presented. For such purpose, the Lorenz problem is reformulated in a classical mechanical form and it turns out to be equivalent to the problem of a damped and forced one dimensional ...
A. d’Anjou   +27 more
core   +1 more source

Saddle–node canard cycles in slow–fast planar piecewise linear differential systems

open access: yesNonlinear Analysis: Hybrid Systems
By applying a singular perturbation approach, canard explosions exhibited by a general family of singularly perturbed planar Piecewise Linear (PWL) differential systems are analyzed. The performed study involves both hyperbolic and non-hyperbolic canard limit cycles appearing after both, a supercritical and a subcritical Hopf bifurcation.
V. Carmona   +2 more
openaire   +4 more sources

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

open access: yesAdvanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

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