This article is concerned with a distributed state estimation problem over sensor networks. The communication links of the sensor networks are subject to bounded time-varying transmission delays. A distributed Kalman filtering algorithm is designed to estimate the state based on a Kalman consensus filtering algorithm. Moreover, sufficient conditions are derived for convergence on estimation errors and the boundedness of error covariances, respectively. Finally, the effectiveness of the designed algorithm is validated by a simulation example.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1109/TCYB.2020.2980582 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
All-solid Conductive Elastomers Bridging Mechanical Performance and Sustainability for Durable and Multifunctional Electronics.
ACS Appl Mater Interfaces
January 2025
State Key Laboratory of Fire Science, University of Science and Technology of China, 443 Huangshan Road, Hefei 230027, P. R.China.
The next generation of stretchable electronics seeks to integrate superior mechanical properties with sustainability and sensing stability. Ionically conductive and liquid-free elastomers have gained recognition as promising candidates, addressing the challenges of evaporation and leakage in gel-based conductors. In this study, a sustainable polymeric deep eutectic system is synergistically integrated with amino-terminated hyperbranched polyamide-modified fibers and aluminum ions, forming a conductive supramolecular network with significant improvements in mechanical performance.
View Article and Find Full Text PDFA multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
View Article and Find Full Text PDFCloud/VPN-Based Remote Control of a Modular Production System Assisted by a Mobile Cyber-Physical Robotic System-Digital Twin Approach.
Sensors (Basel)
January 2025
Department of Automation, "Dunarea de Jos" University of Galati, 800008 Galati, Romania.
This paper deals with a "digital twin" (DT) approach for processing, reprocessing, and scrapping (P/R/S) technology running on a modular production system (MPS) assisted by a mobile cyber-physical robotic system (MCPRS). The main hardware architecture consists of four line-shaped workstations (WSs), a wheeled mobile robot (WMR) equipped with a robotic manipulator (RM) and a mobile visual servoing system (MVSS) mounted on the end effector. The system architecture integrates a hierarchical control system where each of the four WSs, in the MPS, is controlled by a Programable Logic Controller (PLC), all connected via Profibus DP to a central PLC.
View Article and Find Full Text PDFA Feature-Enhanced Small Object Detection Algorithm Based on Attention Mechanism.
Sensors (Basel)
January 2025
School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China.
With the rapid development of AI algorithms and computational power, object recognition based on deep learning frameworks has become a major research direction in computer vision. UAVs equipped with object detection systems are increasingly used in fields like smart transportation, disaster warning, and emergency rescue. However, due to factors such as the environment, lighting, altitude, and angle, UAV images face challenges like small object sizes, high object density, and significant background interference, making object detection tasks difficult.
View Article and Find Full Text PDFIntelligent Intrusion Detection System Against Various Attacks Based on a Hybrid Deep Learning Algorithm.
Sensors (Basel)
January 2025
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia.
The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!