Results 121 to 130 of about 123,227 (279)

Output Feedback Design for Parameter Varying Systems Subject to Persistent Disturbances and Control Rate Constraints

International Journal of Robust and Nonlinear Control, EarlyView.
ABSTRACT This paper develops a framework for designing output feedback controllers for constrained linear parameter‐varying systems that experience persistent disturbances. We specifically propose an incremental parameter‐varying output feedback control law to address control rate constraints, as well as state and control amplitude constraints.
Jackson G. Ernesto, Eugênio B. Castelan, Walter Lucia   +2 more
wiley   +1 more source

The Pier Luigi Nervi's concrete structure of Palazzetto dello Sport: Modeling and dynamic characterization

Structural Concrete, EarlyView.
Abstract This paper presents a numerical and experimental study aimed at the modeling and dynamic characterization of the reinforced concrete structure of the Palazzetto dello Sport in Rome, designed and by Pier Luigi Nervi with Annibale Vitellozzi, and built by Nervi & Bartoli contractors in 1956‐57.
Jacopo Ciambella, Gianluca Ranzi, Francesco Romeo   +2 more
wiley   +1 more source

Boosted unsupervised feature selection for tumor gene expression profiles

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract In an unsupervised scenario, it is challenging but essential to eliminate noise and redundant features for tumour gene expression profiles. However, the current unsupervised feature selection methods treat all samples equally, which tend to learn discriminative features from simple samples.
Yifan Shi, Kaixiang Yang, Mengzhi Wang, Zhiwen Yu, Huanqiang Zeng, Yang Hu   +5 more
wiley   +1 more source

AI‐Powered Anomaly Detection for Secure Internet of Things (IoT): Optimising XGBoost and Deep Learning With Bayesian Optimisation

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Intelligent and adaptive defence systems that can quickly thwart changing cyberthreats are becoming more and more necessary in the dynamic and data‐intensive Internet of things (IoT) environment. Using the NSL‐KDD benchmark dataset, this paper presents an improved anomaly detection system that combines an optimised sequential neural network ...
Seong‐O Shim, Lal Hussain, Mohammed A. Alqarni, Faisal S. Alsubaei, Rasha Jamal Atwah   +4 more
wiley   +1 more source

Adaptive dual-graph learning joint feature selection for EEG emotion recognition

Journal of King Saud University: Computer and Information Sciences
Emotion recognition based on electroencephalography (EEG) has garnered increasing attention for its ability to reflect human emotional states objectively and in real time.
Liangliang Hu, Congming Tan, Yin Tian
doaj   +1 more source

Invariant subspace method for fractional Black-Scholes equations [PDF]

ScienceAsia, 2018
openaire   +1 more source

Structural Feature Selection in Common Spatial Patterns Using Adaptive Sparse Group Lasso

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT With the advancement of brain–computer interfaces (BCI), motor imagery (MI) electroencephalogram (EEG) decoding can greatly benefit from spatial filtering features derived from common spatial patterns (CSP). However, CSP‐based features often exhibit high redundancy and intersubject variability.
Yadi Wang, Jiahao Zhang, Tengfei Zhou, Bingbing Jiang, Jiejiang Chen   +4 more
wiley   +1 more source

An Efficient Method for Transient Temperature Calculation in Oil Natural Transformers Based on the Time‐Space Proper Orthogonal Decomposition

High Voltage, EarlyView.
ABSTRACT A reduced‐order model (ROM) for the temperature field based on time‐space proper orthogonal decomposition (POD) is presented to improve the computational efficiency of transient temperature rise in oil‐immersed power transformers with a complete oil natural convection cooling loop.
Haijuan Lan, Wenhu Tang, Zeyi Zhang, Jiahao Gong, Xiongwen Xu, Goran Strbac   +5 more
wiley   +1 more source

A Multifactor Extension of Linear Discriminant Analysis for Face Recognition under Varying Pose and Illumination

EURASIP Journal on Advances in Signal Processing, 2010
Linear Discriminant Analysis (LDA) and Multilinear Principal Component Analysis (MPCA) are leading subspace methods for achieving dimension reduction based on supervised learning. Both LDA and MPCA use class labels of data samples to calculate subspaces
Park SungWon, Savvides Marios
doaj  

Recognition of Spatiotemporal Feature Images of Zero‐Sequence Voltage for Single‐Phase High‐Impedance Ground Faults Under Complex Conditions

High Voltage, EarlyView.
ABSTRACT Diagnosing high‐impedance ground faults (HIGFs) in distribution networks is extremely challenging because high transition resistance significantly reduces electrical signal strength and unpredictable initial fault phase angles coupled with asymmetric voltage disturbances often lead to misclassification.
Zhengyang Li, Yijia Cao, Chun Chen, Weiyu Wang, Yansha Li, Jinglu Li   +5 more
wiley   +1 more source