AI Medical Compendium Topic:
Time Factors

Clear Filters Showing 451 to 460 of 1860 articles

Developing a hybrid time-series artificial intelligence model to forecast energy use in buildings.

Scientific reports
The development of a reliable energy use prediction model is still difficult due to the inherent complex pattern of energy use data. There are few studies developing a prediction model for the one-day-ahead energy use prediction in buildings and opti...

Recursive Minimum-Variance Filter Design for State-Saturated Complex Networks With Uncertain Coupling Strengths Subject to Deception Attacks.

IEEE transactions on cybernetics
In this article, the recursive filtering problem is investigated for state-saturated complex networks (CNs) subject to uncertain coupling strengths (UCSs) and deception attacks. The measurement signals transmitted via the communication network may su...

Robust Sampled-Data Control for Switched Complex Dynamical Networks With Actuators Saturation.

IEEE transactions on cybernetics
In this article, an aperiodic sampled-data control problem is investigated for polytopic uncertain switched complex dynamical networks subject to actuator saturation. Due to the constraint on the upper bound of the sampling interval being no greater ...

Radar Target Detection Algorithm Using Convolutional Neural Network to Process Graphically Expressed Range Time Series Signals.

Sensors (Basel, Switzerland)
Under the condition of low signal-to-noise ratio, the target detection performance of radar decreases, which seriously affects the tracking and recognition for the long-range small targets. To solve it, this paper proposes a target detection algorith...

Identifying acute ischemic stroke patients within the thrombolytic treatment window using deep learning.

Journal of neuroimaging : official journal of the American Society of Neuroimaging
BACKGROUND AND PURPOSE: Treatment of acute ischemic stroke is heavily contingent upon time, as there is a strong relationship between time clock and tissue progression. Work has established imaging biomarker assessments as surrogates for time since s...

Comprehensive analysis of fixed-time stability and energy cost for delay neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper focuses on comprehensive analysis of fixed-time stability and energy consumed by controller in nonlinear neural networks with time-varying delays. A sufficient condition is provided to assure fixed-time stability by developing a global com...

A novel Lyapunov stability analysis of neutral-type Cohen-Grossberg neural networks with multiple delays.

Neural networks : the official journal of the International Neural Network Society
The major target of this research article is to conduct a new Lyapunov stability analysis of a special model of Cohen-Grossberg neural networks that include multiple delay terms in state variables of systems neurons and multiple delay terms in time d...

Finite-Time Synchronization of Reaction-Diffusion Inertial Memristive Neural Networks via Gain-Scheduled Pinning Control.

IEEE transactions on neural networks and learning systems
For the considered reaction-diffusion inertial memristive neural networks (IMNNs), this article proposes a novel gain-scheduled generalized pinning control scheme, where three pinning control strategies are involved and 2 controller gains can be sche...

Pinning Impulsive Synchronization of Stochastic Delayed Neural Networks via Uniformly Stable Function.

IEEE transactions on neural networks and learning systems
This article investigates the synchronization of stochastic delayed neural networks under pinning impulsive control, where a small fraction of nodes are selected as the pinned nodes at each impulsive moment. By proposing a uniformly stable function a...

Machine learning and the electrocardiogram over two decades: Time series and meta-analysis of the algorithms, evaluation metrics and applications.

Artificial intelligence in medicine
BACKGROUND: The application of artificial intelligence to interpret the electrocardiogram (ECG) has predominantly included the use of knowledge engineered rule-based algorithms which have become widely used today in clinical practice. However, over r...