Results 221 to 230 of about 167,516,375 (307)

Comparative Evaluation of Cross-Sectional Geometric Feature Extraction Algorithms for LiDAR-Based Inclination Detection of Lattice Steel Towers. [PDF]

Sensors (Basel)
Zhou M, Wu G, Qin L, Li S.
europepmc   +1 more source

A Q‐Learning Algorithm to Solve the Two‐Player Zero‐Sum Game Problem for Nonlinear Systems

International Journal of Adaptive Control and Signal Processing, Volume 39, Issue 3, Page 566-581, March 2025.
A Q‐learning algorithm to solve the two‐player zero‐sum game problem for nonlinear systems. ABSTRACT This paper deals with the two‐player zero‐sum game problem, which is a bounded L2$$ {L}_2 $$‐gain robust control problem. Finding an analytical solution to the complex Hamilton‐Jacobi‐Issacs (HJI) equation is a challenging task.
Afreen Islam, Anthony Siming Chen, Guido Herrmann   +2 more
wiley   +1 more source

The Cortical Source of the P300 ERP Generator in the Associative Learning Task: A Consensus of Four Inversion Algorithms. [PDF]

Brain Sci
Kalmagambetov D, Mel'nikov MY, Zholdassova M, Kamzanova A, Abdilmanov D, Datkhabayeva G, Eliassen J, Allendorfer JB, Kustubayeva A.   +8 more
europepmc   +1 more source

Observer‐Based Adaptive Event‐Triggered Tracking Control for Fuzzy TS Systems With Premise Mismatch

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper presents an adaptive logistic event‐triggered observer‐based tracking controller for Takagi‐Sugeno fuzzy systems under constrained inputs and network delays. Leveraging a hybrid LMI and Secretary Bird Optimization approach, this strategy significantly minimizes communication overhead and computational burden while ensuring optimal reference ...
Oussama Djadane, Salama Makni, Mourad Kchaou, Ahmed El Hajjaji   +3 more
wiley   +1 more source

Application of Artificial Intelligence and Machine Learning in Arrhythmia Detection and Pacemaker Data Analysis. [PDF]

Cardiol Res
Shen LH, Xu KQ, Xia PF, Chen J.
europepmc   +1 more source

dynoGP: Deep Gaussian Processes for Dynamic System Identification

International Journal of Adaptive Control and Signal Processing, EarlyView.
This work introduces a novel class of deep models for system identification, dynamical deep Gaussian processes, which combine the strengths of data‐driven methods, such as those based on neural network architectures, with the ability to output a probability distribution for uncertainty representation.
Alessio Benavoli, Marco Forgione, Dario Piga, Marco Zaffalon   +3 more
wiley   +1 more source

Advances in Machine Learning and Deep Learning Algorithm-Assisted Hyperspectral Imaging for Food Quality and Safety Assessment. [PDF]

Foods
Hu L, Dong Y, Hu C, Chen M, Li J.
europepmc   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Applications of Machine Learning in the Research of Heavy Metal(loid)s-Related Risk: A Scoping Review of Methodology. [PDF]

Toxics
Liu Z, Gan Y, Ding C, Wang Z, Yan J, Tan R, Li Y, Luo J, Cui Y.   +8 more
europepmc   +1 more source

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source