Results 61 to 70 of about 1,310 (144)

Quantization‐Based Latin Hypercube Sampling for Dependent Inputs With an Application to Sensitivity Analysis of Environmental Models

Applied Stochastic Models in Business and Industry, Volume 41, Issue 3, May/June 2025.
ABSTRACT Numerical models are essential for comprehending intricate physical phenomena in different domains. To handle their complexity, sensitivity analysis, particularly screening is crucial for identifying influential input parameters. Kernel‐based methods, such as the Hilbert‐Schmidt Independence Criterion (HSIC), are valuable for analyzing ...
Guerlain Lambert, Céline Helbert, Claire Lauvernet   +2 more
wiley   +1 more source

Optimized Hybrid Probabilistic and Geometric Constellation Shaping for Coherent Optical Communication Systems Using End‐to‐End Learning

Advanced Photonics Research, Volume 6, Issue 4, April 2025.
In this article, hybrid probabilistic and geometric constellation shaping to enhance spectral efficiency in coherent optical communication systems, particularly under a Wiener phase noise channel, is investigated. By integrating a two‐stage phase search algorithm with digital signal processing and gradient descent, the method outperforms geometrically ...
Zhiyang Liu, Lu Zhang, Xiaoyu Liu, Shilin Xiao, Weiying Yang, Weisheng Hu   +5 more
wiley   +1 more source

Computational intelligence approaches to robotics, automation, and control [Volume guest editors] [PDF]

, 2015
No abstract ...
Chen, Yi, Gu, Dongbing, Hu, Huosheng, Li, Yun, Xu, Peter, Zhang, Jun   +5 more
core  

l1‐ATSXKF‐based state and bias estimation for non‐linear systems with non‐Gaussian process noise

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
To solve the problem of state and bias estimation for the nonlinear system with non‐Gaussian noise terms, combining the l1 norm and adaptive factors, a series of exogenous Kalman filters (XKF) based state and bias estimation algorithms are proposed. The simulation results show that the proposed algorithms can reduce the influence of the non‐Gaussian ...
Boyu Yang, Xueqin Chen, Fan Wu, Ming Liu
wiley   +1 more source

Basic Types of Coarse-Graining [PDF]

, 2006
We consider two basic types of coarse-graining: the Ehrenfests' coarse-graining and its extension to a general principle of non-equilibrium thermodynamics, and the coarse-graining based on uncertainty of dynamical models and Epsilon-motions (orbits). Non-
Gorban, A. N.
core   +2 more sources

An Improved Weight Adaptive Gaussian Sum Algorithm Based on Sparse‐Grid Quadrature Filter for Non‐Gaussian Models

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
The impetus of this work is to develop a more accurate filter, the Gaussian sum adaptive sparse grid quadrature filter, which can be applied to non‐linear non‐Gaussian systems. Based on the Gaussian sum filter framework, the sparse grid quadrature filter is used as a sub‐filter to complete the filtering, and a weighting function is created to ...
Chen Qian, Enze Zhang, Yang Gao, Qingwei Chen   +3 more
wiley   +1 more source

Secure Dynamic State Estimation of WECS‐Based Networked Microgrids Against Historical Measurement Triggered DoS Attacks

IET Control Theory &Applications, Volume 19, Issue 1, January/December 2025.
This work addresses the issue of rejection delay due to DoS attacks triggered by historical measurements during the transmission of a large amount of measurement data in WECS‐based networked microgrids. We propose a novel robust SRCKF method, designated as MCC‐SRCKF, which incorporates MCC into the SRCKF structure of DSE.
Xiao Hu, Xinghua Liu, Gaoxi Xiao, Zhongmei Pan, Peng Wang   +4 more
wiley   +1 more source

An Efficient Diving Control Scheme for Autonomous Underwater Vehicle Experiencing Actuator Failure: A Multi-Layer Cubature Kalman Filter-Based Nonlinear Model Predictive Control Approach

IEEE Access
Autonomous underwater vehicles (AUVs) are primarily capable of withstanding prolonged periods in unstructured marine environments. These are subject to several uncertainties, including the effects of underwater currents or drift, topography, water ...
Atanu Panda, Subhasish Mahapatra, Siddhartha Vadapalli, Rames C. Panda   +3 more
doaj   +1 more source

Comparing Kalman Filters and Observers for Power System Dynamic State Estimation with Model Uncertainty and Malicious Cyber Attacks

, 2018
Kalman filters and observers are two main classes of dynamic state estimation (DSE) routines. Power system DSE has been implemented by various Kalman filters, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF).
Qi, Junjian, Taha, Ahmad F., Wang, Jianhui   +2 more
core  

Robust Dynamic State Estimation of Power System With Measurement Outliers Based on Parameterized Analytical Cubature Kalman Filter

IET Renewable Power Generation, Volume 19, Issue 1, January/December 2025.
Accurate state estimation is paramount for the smooth operation and management of power systems, significantly contributing to their safety, stability, and reliability. However, the presence of channel noise and outliers stemming from phasor measurement units renders the noise model a deviation from the Gaussian distribution. To mitigate this challenge,
Mingyang Liu, Yanxin Liu, Yi Wang, Venkata Dinavahi, Ze Gao   +4 more
wiley   +1 more source