AI Medical Compendium Topic:
Time Factors

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A Neural Learning Approach for a Data-Driven Nonlinear Error Correction Model.

Computational intelligence and neuroscience
A nonlinear error correction model (ECM) is developed to fit nonlinear relationships between the nonstationary time series in a cointegration relationship. Different from the previous parametric methods, this paper constructs a hybrid neural network ...

Robust exponential stability of discrete-time uncertain impulsive stochastic neural networks with delayed impulses.

Neural networks : the official journal of the International Neural Network Society
This paper is devoted to the study of the robust exponential stability (RES) of discrete-time uncertain impulsive stochastic neural networks (DTUISNNs) with delayed impulses. Using Lyapunov function methods and Razumikhin techniques, a number of suff...

Intra-person multi-task learning method for chronic-disease prediction.

Scientific reports
In the medical field, various clinical information has been accumulated to help clinicians provide personalized medicine and make better diagnoses. As chronic diseases share similar characteristics, it is possible to predict multiple chronic diseases...

State Causality and Adaptive Covariance Decomposition Based Time Series Forecasting.

Sensors (Basel, Switzerland)
Time series forecasting is a very vital research topic. The scale of time series in numerous industries has risen considerably in recent years as a result of the advancement of information technology. However, the existing algorithms pay little atten...

Predicting the monthly consumption and production of natural gas in the USA by using a new hybrid forecasting model based on two-layer decomposition.

Environmental science and pollution research international
As an efficient, economical, and clean energy, natural gas plays an important role in the development of the new energy revolution. Accurate prediction of natural gas consumption and production can adjust energy deployment in advance, which can ensur...

Coexistence and local stability of multiple equilibrium points for fractional-order state-dependent switched competitive neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
This paper investigates the coexistence and local stability of multiple equilibrium points for a class of competitive neural networks with sigmoidal activation functions and time-varying delays, in which fractional-order derivative and state-dependen...

Fixed-time and prescribed-time synchronization of quaternion-valued neural networks: A control strategy involving Lyapunov functions.

Neural networks : the official journal of the International Neural Network Society
A control strategy containing Lyapunov functions is proposed in this paper. Based on this strategy, the fixed-time synchronization of a time-delay quaternion-valued neural network (QVNN) is analyzed. This strategy is extended to the prescribed-time s...

Predefined-time synchronization of coupled neural networks with switching parameters and disturbed by Brownian motion.

Neural networks : the official journal of the International Neural Network Society
This article focuses on predefined time synchronization problem for a class of signal switching neural networks with time-varying delays. In the network models, we not only consider the coupling characteristics in the following networks, but also con...

Anomaly Detection and Inter-Sensor Transfer Learning on Smart Manufacturing Datasets.

Sensors (Basel, Switzerland)
Smart manufacturing systems are considered the next generation of manufacturing applications. One important goal of the smart manufacturing system is to rapidly detect and anticipate failures to reduce maintenance cost and minimize machine downtime. ...

A Study on Structural Health Monitoring of a Large Space Antenna via Distributed Sensors and Deep Learning.

Sensors (Basel, Switzerland)
Most modern Earth and Universe observation spacecraft are now equipped with large lightweight and flexible structures, such as antennas, telescopes, and extendable elements. The trend of hosting more complex and bigger appendages, essential for high-...