Results 141 to 150 of about 65,516 (291)

Modeling error analysis of stationary linear discrete-time filters [PDF]

The performance of Kalman-type, linear, discrete-time filters in the presence of modeling errors is considered. The discussion is limited to stationary performance, and bounds are obtained for the performance index, the mean-squared error of estimates ...
Patel, R., Toda, M.
core   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Graph neural network‐based attack prediction for communication‐based train control systems

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract The Advanced Persistent Threats (APTs) have emerged as one of the key security challenges to industrial control systems. APTs are complex multi‐step attacks, and they are naturally diverse and complex. Therefore, it is important to comprehend the behaviour of APT attackers and anticipate the upcoming attack actions.
Junyi Zhao, Tao Tang, Bing Bu, Qichang Li   +3 more
wiley   +1 more source

Adaptive Kalman filtering [PDF]

Analytical Chemistry, 1991
openaire   +1 more source

Combining kernelised autoencoding and centroid prediction for dynamic multi‐objective optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Evolutionary algorithms face significant challenges when dealing with dynamic multi‐objective optimisation because Pareto optimal solutions and/or Pareto optimal fronts change. The authors propose a unified paradigm, which combines the kernelised autoncoding evolutionary search and the centroid‐based prediction (denoted by KAEP), for solving ...
Zhanglu Hou, Juan Zou, Gan Ruan, Yuan Liu, Yizhang Xia   +4 more
wiley   +1 more source

Exact particle flow Daum-Huang filters for mobile robot localization in occupancy grid maps

Complex & Intelligent Systems
In this paper, we present a novel localization algorithm for mobile robots navigating in complex planar environments, a critical capability for various real-world applications such as autonomous driving, robotic assistance, and industrial automation ...
Domonkos Csuzdi, Tamás Bécsi, Péter Gáspár, Olivér Törő   +3 more
doaj   +1 more source

A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The analysis of spatiotemporal data is essential across many fields, such as transportation, meteorology and healthcare. Data gathered in practical applications often suffer from incompleteness due to device failures and network disruptions.
Yakun Chen, Kaize Shi, Zhangkai Wu, Juan Chen, Xianzhi Wang, Julian McAuley, Guandong Xu, Shui Yu   +7 more
wiley   +1 more source

Evolutionary Dynamic Multiobjective Optimisation Assisted by Inverse Regression Tree Predictor

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Dynamic multiobjective optimisation problems (DMOPs) are optimisation problems with multiple conflicting objectives that can change over time. Most dynamic multiobjective optimisation evolutionary algorithms (DMOEAs) attempt to estimate Pareto‐optimal sets (PS) directly in the decision space.
Kai Gao, Lihong Xu
wiley   +1 more source

From Distributed Noisy Data to Event‐Triggered Pinning Observer‐Based Control

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT This paper presents an event‐triggered pinning observer‐based control of unknown large‐scale interconnected systems under false data injection attacks using distributed noisy data without any system identification step. An exogenous system is used to model the false data injection attack.
Xuan Jia, Junfeng Zhang, Haoyue Yang, Wei Xing   +3 more
wiley   +1 more source

A Probability‐Aware AI Framework for Reliable Anti‐Jamming Communication

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Adversarial jamming attacks have increased on communication systems, causing distortion and threatening transmissions. Typical attacks rely on traditional, well‐defined cryptographic protocols and frequency‐hopping techniques. Nevertheless, these techniques become vulnerable when facing intelligent jammers.
Tawfeeq Shawly, Ahmed A. Alsheikhy
wiley   +1 more source