Major Development Under Gaussian Filtering Since Unscented Kalman Filter

来源 :自动化学报:英文版 | 被引量 : 0次 | 上传用户:kuaileyt
下载到本地 , 更方便阅读
声明 : 本文档内容版权归属内容提供方 , 如果您对本文有版权争议 , 可与客服联系进行内容授权或下架
论文部分内容阅读
Filtering is a recursive estimation of hidden states of a dynamic system from noisy measurements.Such problems appear in several branches of science and technology,ranging from target tracking to biomedical monitoring.A commonly practiced approach of filt
其他文献
In this paper, a new paradigm named parallel distance is presented to measure the data information in parallel driving system. As an example, the core variables
Monocular vision-based navigation is a considerable ability for a home mobile robot. However, due to diverse disturbances, helping robots avoid obstacles, espec
RECENT advances in sensing,communication and computing have open the door to the deployment of largescale networks of sensors and actuators that allow fine-grai
Multi-agent systems are usually equipped with open communication infrastructures to improve interactions efficiency,reliability and sustainability.Although tech
The multitrip pickup and delivery problem with time windows and manpower planning(MTPDPTW-MP)determines a set of ambulance routes and finds staff assignment for
The paper proposes a novel approach for formationcontainment control based on a dynamic event-triggering mechanism for multi-agent systems.The leader-leader and
This paper investigates the secure synchronization control problem for a class of cyber-physical systems(CPSs)with unknown system matrices and intermittent deni
In this paper,denial of service(DoS)attack management for destroying the collaborative estimation in sensor networks and minimizing attack energy from the attac
Cyber attacks pose severe threats on synchronization of multi-agent systems.Deception attack,as a typical type of cyber attack,can bypass the surveillance of th
This paper concentrates on asymmetric barrier Lyapunov functions(ABLFs)based on finite-time adaptive neural network(NN)control methods for a class of nonlinear