AI Medical Compendium Topic:
Time Factors

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A New Settling-time Estimation Protocol to Finite-time Synchronization of Impulsive Memristor-Based Neural Networks.

IEEE transactions on cybernetics
In this article, the issues of finite-time synchronization and finite-time adaptive synchronization for the impulsive memristive neural networks (IMNNs) with discontinuous activation functions (DAFs) and hybrid impulsive effects are probed into and e...

Global Stability of Bidirectional Associative Memory Neural Networks With Multiple Time-Varying Delays.

IEEE transactions on cybernetics
This article investigates the global stability of bidirectional associative memory neural networks with discrete and distributed time-varying delays (DBAMNNs). By employing the comparison strategy and inequality techniques, global asymptotic stabilit...

A new predefined-time stability theorem and its application in the synchronization of memristive complex-valued BAM neural networks.

Neural networks : the official journal of the International Neural Network Society
In this paper, two novel and general predefined-time stability lemmas are given and applied to the predefined-time synchronization problem of memristive complex-valued bidirectional associative memory neural networks (MCVBAMNNs). Firstly, different f...

Comprehensive assessment, review, and comparison of AI models for solar irradiance prediction based on different time/estimation intervals.

Scientific reports
Solar energy-based technologies have developed rapidly in recent years, however, the inability to appropriately estimate solar energy resources is still a major drawback for these technologies. In this study, eight different artificial intelligence (...

Fixed-time synchronization of discontinuous competitive neural networks with time-varying delays.

Neural networks : the official journal of the International Neural Network Society
In this article, the fixed-time (FXT) synchronization of discontinuous competitive neural networks (CNNs) involving time-varying delays is investigated. Firstly, two kinds of discontinuous FXT control schemes are proposed and two forms of Lyapunov fu...

Stochastic Stability Analysis for Stochastic Coupled Oscillator Networks with Bidirectional Cross-Dispersal.

Computational intelligence and neuroscience
It is well known that stochastic coupled oscillator network (SCON) has been widely applied; however, there are few studies on SCON with bidirectional cross-dispersal (SCONBC). This paper intends to study stochastic stability for SCONBC. A new and sui...

Prediction of Labor Unemployment Based on Time Series Model and Neural Network Model.

Computational intelligence and neuroscience
With the advent of big data, statistical accounting based on artificial intelligence can realistically reflect the dynamics of labor force and market segmentation. Therefore, based on the combination of machine learning algorithm and traditional stat...

Finite-Time H State Estimation for PDT-Switched Genetic Regulatory Networks With Randomly Occurring Uncertainties.

IEEE/ACM transactions on computational biology and bioinformatics
This article is concerned with the problem of finite-time H state estimation for switched genetic regulatory networks with randomly occurring uncertainties. The persistent dwell-time switching rule, as a more versatile class of switching rules, is co...

An Evaluation of Anomaly Detection and Diagnosis in Multivariate Time Series.

IEEE transactions on neural networks and learning systems
Several techniques for multivariate time series anomaly detection have been proposed recently, but a systematic comparison on a common set of datasets and metrics is lacking. This article presents a systematic and comprehensive evaluation of unsuperv...

Correlation-Based Anomaly Detection Method for Multi-sensor System.

Computational intelligence and neuroscience
In industry, sensor-based monitoring of equipment or environment has become a necessity. Instead of using a single sensor, multi-sensor system is used to fully detect abnormalities in complex scenarios. Recently, physical models, signal processing te...