Results 91 to 100 of about 304,299 (338)

Hopfield Neural Networks for Online Constrained Parameter Estimation With Time‐Varying Dynamics and Disturbances

International Journal of Adaptive Control and Signal Processing, EarlyView.
This paper proposes two projector‐based Hopfield neural network (HNN) estimators for online, constrained parameter estimation under time‐varying data, additive disturbances, and slowly drifting physical parameters. The first is a constraint‐aware HNN that enforces linear equalities and inequalities (via slack neurons) and continuously tracks the ...
Miguel Pedro Silva
wiley   +1 more source

MENGATASI PENCILAN PADA PEMODELAN REGRESI LINEAR BERGANDA DENGAN METODE REGRESI ROBUST PENAKSIR LMS

Barekeng, 2019
Ordinary Least Squares (OLS) is frequent used method for estimating parameters. OLS estimator is not a robust regression procedure for the presence of outliers, so the estimate becomes inappropriate.
Farida Daniel
doaj   +1 more source

Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling

arXiv.org, 2023
Xiuying Wei, Yunchen Zhang, Yuhang Li, Xiangguo Zhang, Ruihao Gong, Jinyang Guo, Xianglong Liu   +6 more
semanticscholar   +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

A Workflow to Accelerate Microstructure‐Sensitive Fatigue Life Predictions

Advanced Engineering Materials, EarlyView.
This study introduces a workflow to accelerate predictions of microstructure‐sensitive fatigue life. Results from frameworks with varying levels of simplification are benchmarked against published reference results. The analysis reveals a trade‐off between accuracy and model complexity, offering researchers a practical guide for selecting the optimal ...
Luca Loiodice, Krzysztof S. Stopka, Michael D. Sangid   +2 more
wiley   +1 more source

T-outlier and a novel dimensionality reduction framework for high dimensional financial time series [PDF]

, 2006
Dongnian Wang, Paul Fortier, Howard Michel, Theophano Mitsa   +3 more
openalex   +1 more source

Enhancing CoFe Catalysts with V2CTX MXene‐Derived Materials for Anion Exchange Membrane Electrolyzers

Advanced Functional Materials, EarlyView.
MXene dervied CoFe composites show increased initial Oxygen Evolution Reaction (OER) activity compared to the pure CoFe and MXene in an Anion Exchange Membrane device. Vanadium vacancies in the MXene plays a role in increased OER activity and hinders Fe leaching in the AEM device over using the pure V2C MXene as a support material for the CoFe ...
Can Kaplan, Karuppasamy Dharmaraj, Thorsten Schultz, Leiqiang Qin, Ningjun Chen, Danielle A. Douglas‐Henry, Bastian Schmiedecke, Merve Buldu‐Akturk, Axel Zuber, Iris Dorbandt, Maximilian Reinhardt, Yael Rodriguez‐Ayllon, Yan Lu, Valeria Nicolosi, Norbert Koch, Johanna Rosen, Michelle P. Browne   +16 more
wiley   +1 more source

A 3D Biofabricated Disease Model Mimicking the Brain Extracellular Matrix Suitable to Characterize Intrinsic Neuronal Network Alterations in the Presence of a Breast Tumor Disseminated to the Brain

Advanced Functional Materials, EarlyView.
A 3D disease model is developed using customized hyaluronic‐acid‐based hydrogels supplemented with extracellular matrix (ECM) proteins resembling brain ECM properties. Neurons, astrocytes, and tumor cells are used to mimic the native brain surrounding.
Esra Türker, Mateo S. Andrade Mier, Jessica Faber, Mike Friedrich, Zan Lamberger, Jeannette Weigelt, Christian Stigloher, Nicoletta Murenu, Natascha Schaefer, Jörg Tessmar, Gregor Lang, Silvia Budday, Katrin G. Heinze, Antje Appelt‐Menzel, Pamela L. Strissel, Reiner Strick, Carmen Villmann   +16 more
wiley   +1 more source

Two aspects on L1-norm adjustment of leveling networks

Revista Brasileira de Cartografia, 2019
L1-norm adjustment corresponds to the minimization of the sum of weighted absolute residuals. Unlike Least Squares, it is a robust estimator, i.e., insensitive to outliers.
Stefano Sampaio Suraci, Leonardo Castro de Oliveira, Ivandro Klein   +2 more
doaj   +1 more source

NMAoutlier: Detecting Outliers in Network Meta-Analysis [PDF]

, 2019
Μαρία Πετροπούλου, Guido Schwarzer, Agapios Panos, Dimitris Mavridis   +3 more
openalex   +1 more source