IEEE transactions on neural networks and learning systems
Oct 5, 2022
Inferring brain-effective connectivity networks from neuroimaging data has become a very hot topic in neuroinformatics and bioinformatics. In recent years, the search methods based on Bayesian network score have been greatly developed and become an e...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article investigates the stability and synchronization of nonautonomous reaction-diffusion neural networks with general time-varying delays. Compared with the existing works concerning reaction-diffusion neural networks, the main innovation of t...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article concerns the problems of synchronization in a fixed time or prespecified time for memristive complex-valued neural networks (MCVNNs), in which the state variables, activation functions, rates of neuron self-inhibition, neural connection ...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
In the brief, delayed impulsive control is investigated for the synchronization of chaotic neural networks. In order to overcome the difficulty that the delays in impulsive control input can be flexible, we utilize the concept of average impulsive de...
IEEE transactions on neural networks and learning systems
Oct 5, 2022
This article is devoted to investigating finite-time synchronization (FTS) for coupled neural networks (CNNs) with time-varying delays and Markovian jumping topologies by using an intermittent quantized controller. Due to the intermittent property, i...
Sensors (Basel, Switzerland)
Oct 2, 2022
This paper investigates the problem of formation fault-tolerant control of multiple quadrotors (QRs) for a mobile sensing oriented application. The QRs subject to faults, input saturation and time-varying delays can be controlled to perform a target-...
International journal of environmental research and public health
Sep 30, 2022
The coronavirus disease 2019 (COVID-19) has spread rapidly around the world since 2020, with a significant fatality rate. Until recently, numerous countries were unable to adequately control the pandemic. As a result, COVID-19 trend prediction has be...
Computational intelligence and neuroscience
Sep 28, 2022
Intrusion detection systems examine the computer or network for potential security vulnerabilities. Time series data is real-valued. The nature of the data influences the type of anomaly detection. As a result, network anomalies are operations that d...
Computational intelligence and neuroscience
Sep 27, 2022
In this paper, the globally asymptotic synchronization of multi-layer neural networks is studied via aperiodically intermittent control. Due to the property of intermittent control, it is very hard to deal with the effect of time-varying delays and a...
Neural networks : the official journal of the International Neural Network Society
Sep 23, 2022
We propose a novel bootstrap procedure for time series data based on Generative Adversarial networks (GANs). We show that the dynamics of common stationary time series processes can be learned by GANs and demonstrate that GANs trained on a single sam...