Results 51 to 60 of about 303,155 (330)
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Accurate localization of epileptogenic tubers (ETs) in patients with tuberous sclerosis complex (TSC) is essential but challenging, as these tubers lack distinct pathological or genetic markers to differentiate them from other cortical tubers.
Tinghong Liu +11 more
wiley +1 more source
Robust Learning Control for Tank Gun Control Servo Systems Under Alignment Condition
IEEE Access, 2019 This paper proposes an adaptive learning control scheme to solve high-precision velocity tracking problem for tank gun control servo systems. Lyapunov approach is used to design the learning controller, with alignment condition used to cope with initial ...
Guangming Zhu +3 more
doaj +1 more source
Domain adaptation of weighted majority votes via perturbed variation-based self-labeling
, 2014 In machine learning, the domain adaptation problem arrives when the test (target) and the train (source) data are generated from different distributions.
Morvant, Emilie
core +3 more sources
Arthritis Care &Research, EarlyView.Objective A patient‐centered approach for chronic disease management, including systemic lupus erythematosus (SLE), aligns treatment with patients’ values and preferences, leading to improved outcomes. This paper summarizes how patient experiences, perspectives, and priorities informed the American College of Rheumatology (ACR) 2024 Lupus Nephritis (LN)
Shivani Garg +20 more
wiley +1 more source
A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems
International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam +2 more
wiley +1 more source
An Observer-Based Adaptive Iterative Learning Control Using Filtered-FNN Design for Robotic Systems
Advances in Mechanical Engineering, 2014 An observer-based adaptive iterative learning control using a filtered fuzzy neural network is proposed for repetitive tracking control of robotic systems.
Ying-Chung Wang, Chiang-Ju Chien
doaj +1 more source
Frontiers in Physics, 2023 A new adaptive iterative learning control (AILC) scheme is proposed to solve the finite-time hybrid function projective synchronization (HFPS) problem of chaotic systems with unknown periodic time-varying parameters.
Chunli Zhang +6 more
doaj +1 more source
Stochastic Feedback Control of Systems with Unknown Nonlinear Dynamics
, 2017 This paper studies the stochastic optimal control problem for systems with unknown dynamics. First, an open-loop deterministic trajectory optimization problem is solved without knowing the explicit form of the dynamical system.
Chakravorty, Suman +2 more
core +1 more source
IET Control Theory & Applications, 2021 In this paper, to fully utilize the urban traffic flow characteristics of similarity and repeatability without using a mathematical traffic model, a data-driven urban traffic control strategy based on model-free adaptive iterative learning control (MFAILC ...
Dai Li, Z. Hou
semanticscholar +1 more source
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source