Neural networks : the official journal of the International Neural Network Society
Mar 10, 2022
This paper studies the Lyapunov stability of nonlinear systems and the synchronization of complex neural networks in the framework of event-triggered delayed impulsive control (ETDIC), where the effect of time delays in impulses is fully considered. ...
International journal of neural systems
Mar 8, 2022
Nonlinear spiking neural P (NSNP) systems are a recently developed theoretical model, which is abstracted by nonlinear spiking mechanism of biological neurons. NSNP systems have a nonlinear structure and the potential to describe nonlinear dynamic sy...
Neural networks : the official journal of the International Neural Network Society
Mar 8, 2022
In this paper, an array of discrete-time coupled complex-valued neural networks (CVNNs) with random system parameters and time-varying delays are introduced. The stochastic fluctuations of system parameters, which are characterized by a set of random...
IEEE transactions on pattern analysis and machine intelligence
Mar 4, 2022
Incomplete time series classification (ITSC) is an important issue in time series analysis since temporal data often has missing values in practical applications. However, integrating imputation (replacing missing data) and classification within a mo...
IEEE transactions on neural networks and learning systems
Feb 28, 2022
This brief is concerned with the stability of a neural network with a time-varying delay using the quadratic function negative-definiteness approach reported recently. A more general reciprocally convex combination inequality is taken to introduce so...
Computational intelligence and neuroscience
Feb 27, 2022
The nonstationary time series is generated in various natural and man-made systems, of which the prediction is vital for advanced control and management. The neural networks have been explored in the time series prediction, but the problem remains in...
Journal of healthcare engineering
Feb 23, 2022
This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multiscale sampling frequency of multisource heterogeneous data. The proposed model also demonstrates its su...
Neural networks : the official journal of the International Neural Network Society
Feb 22, 2022
This study deals with the finite-time synchronization problem of a class of switched complex dynamical networks (CDNs) with distributed coupling delays via sampled-data control. First, the dynamical model is studied with coupling delays in more detai...
Sensors (Basel, Switzerland)
Feb 15, 2022
Frost forecast is an important issue in climate research because of its economic impact on several industries. In this study, we propose GRAST-Frost, a graph neural network (GNN) with spatio-temporal architecture, which is used to predict minimum tem...
BMC bioinformatics
Feb 15, 2022
BACKGROUND: Nerve discharge is the carrier of information transmission, which can reveal the basic rules of various nerve activities. Recognition of the nerve discharge rhythm is the key to correctly understand the dynamic behavior of the nervous sys...