Results 261 to 270 of about 412,258 (327)

Ellipsoid‐Based Interval‐Type Uncertainty Model Updating Based on Riemannian Manifold and Gaussian Process Model

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao, Qintao Guo, Jin Zhou, Cheng Yi   +3 more
wiley   +1 more source

Event-Triggered Secure Control Design Against False Data Injection Attacks via Lyapunov-Based Neural Networks. [PDF]

Sensors (Basel)
Kutlucan NK, Ucun L, Dasdemir J.
europepmc   +1 more source

Trajectory Control of Manipulator Robots With Uncertainties: A Saturated Continuous Integral Sliding Mode Approach

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT This study addresses the trajectory tracking control for manipulator robots with uncertainties. The main objective is to ensure that the robot follows a desired trajectory despite the presence of uncertainties/disturbances and considering control input constraints. The approach is developed in the framework of continuous integral sliding modes.
Emanuel Ortiz‐Ortiz, Juan Eduardo Velázquez‐Velázquez, Ramón Silva‐Ortigoza, Rosalba Galván‐Guerra   +3 more
wiley   +1 more source

Resource-efficient quantum correlation measurements via multicopy neural network methods. [PDF]

Sci Rep
Tulewicz P, Bartkiewicz K, Miranowicz A, Nori F.   +3 more
europepmc   +1 more source

Scheduling Bodyguards

Naval Research Logistics (NRL), EarlyView.
ABSTRACT Security agencies around the world use bodyguards to protect government officials and public figures. In this paper, we consider a two‐person zero‐sum game between a defender who allocates such bodyguards to protect several targets and an attacker who chooses one target to attack.
Loe Schlicher, Kyle Y. Lin, Moshe Kress
wiley   +1 more source

Personalized Differential Privacy for Ridge Regression Under Output Perturbation

Naval Research Logistics (NRL), EarlyView.
ABSTRACT The increased application of machine learning (ML) in sensitive domains requires protecting the training data through privacy frameworks, such as differential privacy (DP). Traditional DP enforces a uniform privacy level ε$$ \varepsilon $$, which bounds the maximum privacy loss that each data point in the dataset is allowed to incur.
Krishna Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani   +3 more
wiley   +1 more source

Analog optical computer for AI inference and combinatorial optimization. [PDF]

Nature
Kalinin KP, Gladrow J, Chu J, Clegg JH, Cletheroe D, Kelly DJ, Rahmani B, Brennan G, Canakci B, Falck F, Hansen M, Kleewein J, Kremer H, O'Shea G, Pickup L, Rajmohan S, Rowstron A, Ruhle V, Braine L, Khedekar S, Berloff NG, Gkantsidis C, Parmigiani F, Ballani H.   +23 more
europepmc   +1 more source

Research on LPV-H_∞ control strategy of magnetorheological semi-active suspension with air spring. [PDF]

Sci Rep
Li G, Zhang S, Li J, Huang Q, Liu Q, Zhong L, Sun W, Ding R, Hu G, Deng J.   +9 more
europepmc   +1 more source

Some new QEC MDS codes with large minimum distance. [PDF]

Sci Rep
Li L, Tian F, Cao Z, Liu L.
europepmc   +1 more source

Experimental entanglement swapping through single-photon χ⁽²⁾ nonlinearity. [PDF]

Nat Commun
Tsujimoto Y, Wakui K, Kishimoto T, Miki S, Yabuno M, Terai H, Fujiwara M, Kato G.   +7 more
europepmc   +1 more source