Results 51 to 60 of about 8,582 (299)

Dynamics Between Malaysian Equity Market And Macroeconomic Variables : An Application Of Kalman Filter Model With Heteroskedastic Error [QA402.3. C514 2007 f rb]. [PDF]

, 2006
Sejak diperkenalkan oleh Kalman dan Bucy (1960), model penapis Kalman telah mendapat penggunaan yang luas dalam dalam program ruang angkasa dan bidang kejuteraan kawalan.
Cheah, Lee Han, Cheah, Lee Hen
core  

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Unscented Kalman Filter Based Attitude Estimation of a Quadrotor

Havacılık ve Uzay Teknolojileri Dergisi, 2021
Quadrotors are well - known unmanned aerial vehicle structures that have some advantages such as hovering, vertical take – off and landing, and low – speed flight. On the other hand, quadrotors are subjected to modeling and sensor uncertainties that lead
Aziz Kaba
doaj  

A Bayesian approach to distributed optimal filtering over a ring network

Measurement: Sensors, 2021
This paper is concerned with the state estimation over a sensor network. Distributed estimation algorithms enable us to estimate the system state using the information from other sensors, even when the state is not completely observable from some sensors.
Akihiro Tsuji, Asuka Ohashi, Kiyotsugu Takaba   +2 more
doaj   +1 more source

Distributed H∞-consensus filtering in sensor networks with multiple missing measurements: The finite-horizon case

, 2010
The official published version of the article can be found at the link below.This paper is concerned with a new distributed H∞-consensus filtering problem over a finite-horizon for sensor networks with multiple missing measurements.
Zidong Wang, Wang, Z, Hung, YS, Hung, Y, Y.S. Hung, Bo Shen, Shen, B   +6 more
core   +1 more source

Distributed H-infinity filtering for polynomial nonlinear stochastic systems in sensor networks [PDF]

, 2010
Copyright [2010] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Zidong Wang, Wang, Z, Y. S. Hung, Graziano Chesi, Hung, YS, Chesi, G, Hung, Y, Bo Shen, Shen, B   +8 more
core   +1 more source

Experimental Demonstration of Temporally Aware Fault‐Tolerant Sensor Fusion Using Memristive Associative Learning

Advanced Electronic Materials, EarlyView.
In dynamic driving scenarios, the proposed approach ensures only temporally aligned sensor inputs to make driving decisions, preventing false activations. By enabling selective hardware‐level learning, it achieves fast, reliable responses under noisy conditions.
Kapil Bhardwaj, Ashfak Nehal, Dmitrii Semenov, Roman Sotner, Sayani Majumdar   +4 more
wiley   +1 more source

Distributed Acoustic Source Tracking in Noisy and Reverberant Environments With Distributed Microphone Networks

IEEE Access, 2020
In this paper, an improved distributed unscented Kalman particle filter (DUKPF) is proposed for the problem of tracking a single moving acoustic source in noisy and reverberant environments with distributed microphone networks.
Qiaoling Zhang, Weiwei Zhang, Jie Feng, Roubing Tang   +3 more
doaj   +1 more source

Dictionary‐based weak‐form training for noise‐robust series hybrid models with multiplicative unknowns

AIChE Journal, EarlyView.
ABSTRACT Hybrid modeling combines first‐principles equations with a data‐driven subcomponent. Training for the data‐driven part is sensitive to measurement noise when training targets are constructed using pointwise time derivatives. Beyond differentiation errors, hybrid models involve solving an inverse problem to estimate the data‐driven term, which ...
Hangjun Cho, Akshay Kudva, Parth Shah, Dongheon Lee, Joseph Sang‐Il Kwon   +4 more
wiley   +1 more source

Considering spatiotemporal evolutionary information in dynamic multi‐objective optimisation

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Preserving population diversity and providing knowledge, which are two core tasks in the dynamic multi‐objective optimisation (DMO), are challenging since the sampling space is time‐ and space‐varying. Therefore, the spatiotemporal property of evolutionary information needs to be considered in the DMO.
Qinqin Fan, Min Jiang, Wentao Huang, Qingchao Jiang   +3 more
wiley   +1 more source