Genome Mining in Glass Chemistry Using Linear Component Analysis of Ion Conductivity Data.
Sign Up to like & getrecommendations! Published in 2023 at "Advanced science"
DOI: 10.1002/advs.202301435
Abstract: Understanding the multivariate origin of physical properties is particularly complex for polyionic glasses. As a concept, the term genome has been used to describe the entirety of structure-property relations in solid materials, based on functional… read more here.
Keywords: linear component; chemistry; conductivity; genome ... See more keywords
Self‐Adaptive Quantum Kernel Principal Component Analysis for Compact Readout of Chemiresistive Sensor Arrays
Sign Up to like & getrecommendations! Published in 2024 at "Advanced Science"
DOI: 10.1002/advs.202411573
Abstract: The rapid growth of Internet of Things (IoT) devices necessitates efficient data compression techniques to manage the vast amounts of data they generate. Chemiresistive sensor arrays (CSAs), a simple yet essential component in IoT systems,… read more here.
Keywords: principal component; sensor; component analysis; sensor arrays ... See more keywords
Application of independent component analysis with semi‐supervised Laplacian regularization kernel density estimation
Sign Up to like & getrecommendations! Published in 2018 at "Canadian Journal of Chemical Engineering"
DOI: 10.1002/cjce.23067
Abstract: In this study, fault detection and fault reconstruction methods are developed using matrix factorization of component vectors obtained with independent component analysis (ICA). Two monitoring statistics are used for fault detection in a detailed analysis… read more here.
Keywords: fault; independent component; semi supervised; analysis ... See more keywords
Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity
Sign Up to like & getrecommendations! Published in 2024 at "Human Brain Mapping"
DOI: 10.1002/hbm.26682
Abstract: Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA)… read more here.
Keywords: principal component; brain; pca; component analysis ... See more keywords
Evaluation of principal component analysis image denoising on multi‐exponential MRI relaxometry
Sign Up to like & getrecommendations! Published in 2019 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.27658
Abstract: Multi‐exponential relaxometry is a powerful tool for characterizing tissue, but generally requires high image signal‐to‐noise ratio (SNR). This work evaluates the use of principal‐component‐analysis (PCA) denoising to mitigate these SNR demands and improve the precision… read more here.
Keywords: multi exponential; image; principal component; relaxometry ... See more keywords
Principal component analysis of hybrid functional and vector data.
Sign Up to like & getrecommendations! Published in 2021 at "Statistics in medicine"
DOI: 10.1002/sim.9117
Abstract: We propose a practical principal component analysis (PCA) framework that provides a nonparametric means of simultaneously reducing the dimensions of and modeling functional and vector (multivariate) data. We first introduce a Hilbert space that combines… read more here.
Keywords: vector; hybrid functional; principal component; vector data ... See more keywords
Sparse common component analysis for multiple high-dimensional datasets via noncentered principal component analysis
Sign Up to like & getrecommendations! Published in 2018 at "Statistical Papers"
DOI: 10.1007/s00362-018-1045-6
Abstract: There is currently much discussion about the analysis of multiple datasets from different groups, among which especially identifying a common basic structure of multiple groups has drawn a large amount of attention. In order to… read more here.
Keywords: common component; sparse common; analysis; cca ... See more keywords
Random permutation principal component analysis for cancelable biometric recognition
Sign Up to like & getrecommendations! Published in 2017 at "Applied Intelligence"
DOI: 10.1007/s10489-017-1117-7
Abstract: Although biometrics is being increasingly used across the world, it also raises concerns over privacy and security of the enrolled identities. This is due to the fact that biometrics are not cancelable and if compromised… read more here.
Keywords: principal component; cancelable biometric; biometrics; random permutation ... See more keywords
Principal component analysis based on block-norm minimization
Sign Up to like & getrecommendations! Published in 2018 at "Applied Intelligence"
DOI: 10.1007/s10489-018-1382-0
Abstract: Principal Component Analysis (PCA) has attracted considerable interest for years in the studies of image recognition. So far, several state-of-the-art PCA-based robust feature extraction techniques have been proposed, such as PCA-L1 and R1-PCA. Since those… read more here.
Keywords: block; principal component; pca; block norm ... See more keywords
How does Independent Component Analysis Preprocessing Affect EEG Microstates?
Sign Up to like & getrecommendations! Published in 2025 at "Brain Topography"
DOI: 10.1007/s10548-024-01098-4
Abstract: Over recent years, electroencephalographic (EEG) microstates have been increasingly used to investigate, at a millisecond scale, the temporal dynamics of large-scale brain networks. By studying their topography and chronological sequence, microstates research has contributed to… read more here.
Keywords: eeg microstates; brain; topography; microstate ... See more keywords
MWRSPCA: online fault monitoring based on moving window recursive sparse principal component analysis
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Intelligent Manufacturing"
DOI: 10.1007/s10845-020-01721-8
Abstract: This paper proposes a moving window recursive sparse principal component analysis (MWRSPCA)-based online fault monitoring scheme, aim at providing an online fault monitoring solution for large-scale complex industrial processes (e.g., chemical industry processes) with time-varying… read more here.
Keywords: fault; sparse principal; principal component; monitoring ... See more keywords