Neural networks : the official journal of the International Neural Network Society
Feb 4, 2015
This paper concerns the pth moment synchronization in an array of generally coupled memristor-based neural networks with time-varying discrete delays, unbounded distributed delays, as well as stochastic perturbations. Hybrid controllers are designed ...
IEEE transactions on neural networks and learning systems
Dec 19, 2014
This paper presents a tracking control methodology for a class of uncertain nonlinear systems subject to input saturation constraint and external disturbances. Unlike most previous approaches on saturated systems, which assumed affine nonlinear syste...
IEEE transactions on neural networks and learning systems
Dec 18, 2014
Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-base...
IEEE transactions on neural networks and learning systems
Dec 4, 2014
In this paper, a dynamic surface control (DSC) scheme is proposed for a class of uncertain strict-feedback nonlinear systems in the presence of input saturation and unknown external disturbance. The radial basis function neural network (RBFNN) is emp...
Bioorganic & medicinal chemistry letters
Nov 7, 2014
The great majority of molecular modeling tasks require the construction of a model that is then used to evaluate new compounds. Although various types of these models exist, at some stage, they all use knowledge about the activity of a given group of...
IEEE transactions on neural networks and learning systems
Oct 8, 2014
An approximate online equilibrium solution is developed for an N -player nonzero-sum game subject to continuous-time nonlinear unknown dynamics and an infinite horizon quadratic cost. A novel actor-critic-identifier structure is used, wherein a robus...
IEEE transactions on neural networks and learning systems
Sep 25, 2014
This paper addresses the problem of globally stable direct adaptive backstepping neural network (NN) tracking control design for a class of uncertain strict-feedback systems under the assumption that the accuracy of the ultimate tracking error is giv...
IEEE transactions on neural networks and learning systems
Aug 6, 2014
This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by ne...
Studies in health technology and informatics
Apr 24, 2025
INTRODUCTION: Predictive models hold significant potential in healthcare, but their adoption in clinical settings is hampered by limited trust due to their inability to recognize when presented with unfamiliar data. Estimating knowledge uncertainty (...
The journal of applied laboratory medicine
Mar 3, 2025
BACKGROUND: Interest in prediction models, including machine learning (ML) models, based on laboratory data has increased tremendously. Uncertainty in laboratory measurements and predictions based on such data are inherently intertwined. This study d...