Results 61 to 70 of about 27,115 (309)
Ellipsoidal Subspace Support Vector Data Description
IEEE Access, 2020 In this paper, we propose a novel method for transforming data into a low-dimensional space optimized for one-class classification. The proposed method iteratively transforms data into a new subspace optimized for ellipsoidal encapsulation of target ...
Fahad Sohrab +3 more
doaj +1 more source
Trust‐region filter algorithms utilizing Hessian information for gray‐box optimization
AIChE Journal, EarlyView.Abstract Optimizing industrial processes often involves gray‐box models that couple algebraic glass‐box equations with black‐box components lacking analytic derivatives. Such systems challenge derivative‐based solvers. The classical trust‐region filter (TRF) algorithm provides a robust framework but requires extensive parameter tuning and numerous ...
Gul Hameed +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This work introduces a novel framework for identifying non‐small cell lung cancer biomarkers from hundreds of volatile organic compounds in breath, analyzed via gas chromatography‐mass spectrometry. This method integrates generative data augmentation and multi‐view feature selection, providing a stable and accurate solution for biomarker discovery in ...
Guancheng Ren +10 more
wiley +1 more source
Generalized Portmanteau Tests Based on Subspace Methods
Revista Colombiana de Estadística, 2013 The problem of diagnostic checking is tackled from the perspective of the subspace methods. Two statistics are presented and their asymptotic distributions are derived under the null hypothesis.
ALFREDO GARCÍA-HIERNAUX
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Signal Subspace Speech Enhancement with Oblique Projection and Normalization [PDF]
Radioengineering, 2017 In this paper, a subspace speech enhancement method handling colored noise using oblique projection is proposed. Perceptual features and variance normalization are used to reduce residual noise and improve speech intelligibility of the output. Initially,
S. Surendran, T. K. Kumar
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Advanced Intelligent Discovery, EarlyView.This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah +3 more
wiley +1 more source
Tongxin xuebao, 2021 Considering the impact of high dimensional data redundancy and noise interference on multiview subspace clustering, a robust multiview subspace clustering method based on multi-kernel low redundancy representation learning was proposed.Firstly, by ...
Ao LI +5 more
doaj +2 more sources
Advanced Intelligent Discovery, EarlyView.This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
Joint Subspace and Low-Rank Coding Method for Makeup Face Recognition [PDF]
, 2021 Jianwei Lu +3 more
openalex +1 more source
DS/CDMA Multiuser Detectors Based on Subspace Methods
Semina: Ciências Exatas e Tecnológicas, 2006 In this work blind and group-blind (Bld-MuD and SBld-MuD, respectively) multiuser detectors (MuD) are analyzed from the point of view of the trade-off between performance versus complexity; specifically, the blind and group-blind detectors are ...
Paul Jean Etienne Jeszensky +2 more
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