AIMC Topic: Time Factors

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Multistability analysis of delayed recurrent neural networks with a class of piecewise nonlinear activation functions.

Neural networks : the official journal of the International Neural Network Society
This paper studies the multistability of delayed recurrent neural networks (DRNNs) with a class of piecewise nonlinear activation functions. The coexistence as well as the stability of multiple equilibrium points (EPs) of DRNNs are proved. With the B...

Data Pre-Processing Using Neural Processes for Modeling Personalized Vital-Sign Time-Series Data.

IEEE journal of biomedical and health informatics
Clinical time-series data retrieved from electronic medical records are widely used to build predictive models of adverse events to support resource management. Such data is often sparse and irregularly-sampled, which makes it challenging to use many...

Real-Time Hierarchical Classification of Time Series Data for Locomotion Mode Detection.

IEEE journal of biomedical and health informatics
OBJECTIVE: Accurate real-time estimation of motion intent is critical for rendering useful assistance using wearable robotic prosthetic and exoskeleton devices during user-initiated motions. We aim to evaluate hierarchical classification as a strateg...

A Novel Encoder-Decoder Model for Multivariate Time Series Forecasting.

Computational intelligence and neuroscience
The time series is a kind of complex structure data, which contains some special characteristics such as high dimension, dynamic, and high noise. Moreover, multivariate time series (MTS) has become a crucial study in data mining. The MTS utilizes the...

Deep learning time series prediction models in surveillance data of hepatitis incidence in China.

PloS one
BACKGROUND: Precise incidence prediction of Hepatitis infectious disease is critical for early prevention and better government strategic planning. In this paper, we presented different prediction models using deep learning methods based on the month...

A Hidden Markov Ensemble Algorithm Design for Time Series Analysis.

Sensors (Basel, Switzerland)
With the exponential growth of data, solving classification or regression tasks by mining time series data has become a research hotspot. Commonly used methods include machine learning, artificial neural networks, and so on. However, these methods on...

Lightweight Long Short-Term Memory Variational Auto-Encoder for Multivariate Time Series Anomaly Detection in Industrial Control Systems.

Sensors (Basel, Switzerland)
Heterogeneous cyberattacks against industrial control systems (ICSs) have had a strong impact on the physical world in recent decades. Connecting devices to the internet enables new attack surfaces for attackers. The intrusion of ICSs, such as the ma...

Finite-time H∞ synchronization control for coronary artery chaos system with input and state time-varying delays.

PloS one
This is the first time for studying the issue of finite-time H∞ synchronization control for the coronary artery chaos system (CACS) with input and state time-varying delays. Feedback control is planned for finite-time of synchronization CACS. By cons...

Some Novel Results on Stability Analysis of Generalized Neural Networks With Time-Varying Delays via Augmented Approach.

IEEE transactions on cybernetics
This article proposes three new methods to enlarge the feasible region for guaranteeing stability for generalized neural networks having time-varying delays based on the Lyapunov method. First, two new zero equalities in which three states are augmen...

Modified BBO-Based Multivariate Time-Series Prediction System With Feature Subset Selection and Model Parameter Optimization.

IEEE transactions on cybernetics
Multivariate time-series prediction is a challenging research topic in the field of time-series analysis and modeling, and is continually under research. The echo state network (ESN), a type of efficient recurrent neural network, has been widely used...