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A survey on feature selection techniques based on filtering methods for cyber attack detection
Cyber attack detection technology plays a vital role today, since cyber attacks have been
causing great harm and loss to organizations and individuals. Feature selection is a …
causing great harm and loss to organizations and individuals. Feature selection is a …
Finite-time event-triggered control for semi-Markovian switching cyber-physical systems with FDI attacks and applications
This paper addresses the finite-time event-triggered control problem for nonlinear semi-
Markovian switching cyber-physical systems (S-MSCPSs) under false data injection (FDI) …
Markovian switching cyber-physical systems (S-MSCPSs) under false data injection (FDI) …
DeepYield: A combined convolutional neural network with long short-term memory for crop yield forecasting
Crop yield forecasting is of great importance to crop market planning, crop insurance,
harvest management, and optimal nutrient management. Commonly used approaches for …
harvest management, and optimal nutrient management. Commonly used approaches for …
Joint parameter and time-delay estimation for a class of nonlinear time-series models
Nonlinear time-series modeling is fundamental to a wide variety of control and prediction
problems. This letter focuses on the joint parameter and time-delay estimation for an …
problems. This letter focuses on the joint parameter and time-delay estimation for an …
A survey on hidden Markov jump systems: Asynchronous control and filtering
In recent years, the problems of asynchronous control and filtering for Markov jump systems
(MJSs) have received great research attention from scientific and engineering communities …
(MJSs) have received great research attention from scientific and engineering communities …
Towards deep probabilistic graph neural network for natural gas leak detection and localization without labeled anomaly data
Deep learning has been widely applied to automated leakage detection and location of
natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial …
natural gas pipe networks. Prevalent deep learning approaches do not consider the spatial …
Finite-region asynchronous H∞ filtering for 2-D Markov jump systems in Roesser model
This paper addresses finite-region asynchronous H∞ filtering for a class of two-dimensional
Markov jump systems (2-D MJSs). A mathematical model is established using the Roesser …
Markov jump systems (2-D MJSs). A mathematical model is established using the Roesser …
Modified particle filtering‐based robust estimation for a networked control system corrupted by impulsive noise
X Wang, F Ding - International Journal of Robust and Nonlinear …, 2022 - Wiley Online Library
The non‐Gaussian characteristic of the impulsive noise significantly degrades the
performance of the‐norm‐based identification algorithms. To overcome the negative effects …
performance of the‐norm‐based identification algorithms. To overcome the negative effects …
Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by Gaussian-guided latent alignment
In this paper, we focus on the unsupervised domain adaptation problem where an
approximate inference model is to be learned from a labeled data domain and expected to …
approximate inference model is to be learned from a labeled data domain and expected to …
Finite-time H2/H∞ control for linear Itô stochastic Markovian jump systems with Brownian motion and Poisson jumps
This paper is concerned with the problems of finite-time H 2/H∞ control for linear stochastic
Markovian jump systems (SMJSs) suffered from external disturbance and both Brownian …
Markovian jump systems (SMJSs) suffered from external disturbance and both Brownian …