AIMC Topic: Time Factors

Clear Filters Showing 431 to 440 of 2001 articles

Mortality prediction using medical time series on TBI patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Traumatic Brain Injury (TBI) is one of the leading causes of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40%. It is highly heterogeneous both in causes and consequences making more...

An adaptive embedding procedure for time series forecasting with deep neural networks.

Neural networks : the official journal of the International Neural Network Society
Nowadays, solving time series prediction problems is an open and challenging task. Many solutions are based on the implementation of deep neural architectures, which are able to analyze the structure of the time series and to carry out the prediction...

Novel results on asymptotic stability and synchronization of fractional-order memristive neural networks with time delays: The 0<δ≤1 case.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the asymptotic stability and synchronization of fractional-order (FO) memristive neural networks with time delays. Based on the FO comparison principle and inverse Laplace transform method, the novel sufficient conditions for ...

A novel neural network for improved in-hospital mortality prediction with irregular and incomplete multivariate data.

Neural networks : the official journal of the International Neural Network Society
Accurate estimation of in-hospital mortality based on patients' physiological time series data improves the performance of the clinical decision support systems and assists hospital providers in allocating resources. In practice, the data quality iss...

Finite/fixed-time synchronization of inertial memristive neural networks by interval matrix method for secure communication.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the finite/fixed-time synchronization problem of delayed inertial memristive neural networks (DIMNNs) using interval matrix-based methods within a unified control framework. By employing set-valued mapping and differential inc...

Synchronization of coupled switched neural networks subject to hybrid stochastic disturbances.

Neural networks : the official journal of the International Neural Network Society
In this paper, the theoretical analysis on exponential synchronization of a class of coupled switched neural networks suffering from stochastic disturbances and impulses is presented. A control law is developed and two sets of sufficient conditions a...

Adaptive event-triggered extended dissipative synchronization of delayed reaction-diffusion neural networks under deception attacks.

Neural networks : the official journal of the International Neural Network Society
Under spatially averaged measurements (SAMs) and deception attacks, this article mainly studies the problem of extended dissipativity output synchronization of delayed reaction-diffusion neural networks via an adaptive event-triggered sampled-data (A...

Fixed-time periodic stabilization of discontinuous reaction-diffusion Cohen-Grossberg neural networks.

Neural networks : the official journal of the International Neural Network Society
This paper aims to study the fixed-time stabilization of a class of delayed discontinuous reaction-diffusion Cohen-Grossberg neural networks. Firstly, by providing some relaxed conditions containing indefinite functions and based on inequality techni...

Intermediately synchronised brain states optimise trade-off between subject specificity and predictive capacity.

Communications biology
Functional connectivity (FC) refers to the statistical dependencies between activity of distinct brain areas. To study temporal fluctuations in FC within the duration of a functional magnetic resonance imaging (fMRI) scanning session, researchers hav...

Online dynamic ensemble deep random vector functional link neural network for forecasting.

Neural networks : the official journal of the International Neural Network Society
This paper proposes a three-stage online deep learning model for time series based on the ensemble deep random vector functional link (edRVFL). The edRVFL stacks multiple randomized layers to enhance the single-layer RVFL's representation ability. Ea...