Search results for "Alternating least squares"

showing 4 items of 4 documents

Optimisation of chromatographic resolution using objective functions including both time and spectral information.

2014

The optimisation of the resolution in high-performance liquid chromatography is traditionally performed attending only to the time information. However, even in the optimal conditions, some peak pairs may remain unresolved. Such incomplete resolution can be still accomplished by deconvolution, which can be carried out with more guarantees of success by including spectral information. In this work, two-way chromatographic objective functions (COFs) that incorporate both time and spectral information were tested, based on the peak purity (analyte peak fraction free of overlapping) and the multivariate selectivity (figure of merit derived from the net analyte signal) concepts. These COFs are s…

AnalyteMultivariate statisticsChromatographyChromatographyAcetonitrilesTime FactorsResolution (mass spectrometry)ChemistryOrganic ChemistryOrthographic projectionWaterGeneral MedicineBiochemistrySignalChemistry Techniques AnalyticalAnalytical ChemistryPhenolsAlternating least squaresFigure of meritDeconvolutionJournal of chromatography. A
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Fast Implementation of Double-coupled Nonnegative Canonical Polyadic Decomposition

2019

Real-world data exhibiting high order/dimensionality and various couplings are linked to each other since they share some common characteristics. Coupled tensor decomposition has become a popular technique for group analysis in recent years, especially for simultaneous analysis of multi-block tensor data with common information. To address the multiblock tensor data, we propose a fast double-coupled nonnegative Canonical Polyadic Decomposition (FDC-NCPD) algorithm in this study, based on the linked CP tensor decomposition (LCPTD) model and fast Hierarchical Alternating Least Squares (Fast-HALS) algorithm. The proposed FDCNCPD algorithm enables simultaneous extraction of common components, i…

Computer sciencelinked CP tensor decomposition (LCPTD)02 engineering and technologySignal-to-noise ratiotensor decompositionConvergence (routing)0202 electrical engineering electronic engineering information engineeringDecomposition (computer science)TensorHigh orderta113konvergenssiconvergencesignal to noise ratio020206 networking & telecommunicationsbrain modelinghierarchical alternating least squares (HALS)Alternating least squaresCore (graph theory)coupled tensor decomposition020201 artificial intelligence & image processingAlgorithmsignal processing algorithmselectroencephalographymathematical modelCurse of dimensionality
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Combining Pharmacokinetics and Vibrational Spectroscopy: MCR-ALS Hard-and-Soft Modelling of Drug Uptake In Vitro Using Tailored Kinetic Constraints

2022

Raman microspectroscopy is a label-free technique which is very suited for the investigation of pharmacokinetics of cellular uptake, mechanisms of interaction, and efficacies of drugs in vitro. However, the complexity of the spectra makes the identification of spectral patterns associated with the drug and subsequent cellular responses difficult. Indeed, multivariate methods that relate spectral features to the inoculation time do not normally take into account the kinetics involved, and important theoretical information which could assist in the elucidation of the relevant spectral signatures is excluded. Here, we propose the integration of kinetic equations in the modelling of drug uptake…

Multivariate Curve Resolution-Alternating Least SquaresBiological and Chemical PhysicsSystems BiologyMultivariate Curve Resolution-Alternating Least Squares; pharmacokinetics; Raman microspectroscopy; chemometricsGeneral MedicineSpectrum Analysis RamanRaman microspectroscopyKineticsMultivariate AnalysisHumansPharmacokineticsLeast-Squares AnalysisChemometricsBiochemistry Biophysics and Structural Biology
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Generalization of Linked Canonical Polyadic Tensor Decomposition for Group Analysis

2019

Real-world data are often linked with each other since they share some common characteristics. The mutual linking can be seen as a core driving force of group analysis. This study proposes a generalized linked canonical polyadic tensor decomposition (GLCPTD) model that is well suited to exploiting the linking nature in multi-block tensor analysis. To address GLCPTD model, an efficient algorithm based on hierarchical alternating least squa res (HALS) method is proposed, termed as GLCPTD-HALS algorithm. The proposed algorithm enables the simultaneous extraction of common components, individual components and core tensors from tensor blocks. Simulation experiments of synthetic EEG data analysi…

canonical polyadicComputer scienceGeneralizationNoise reductionlinked tensor decomposition020206 networking & telecommunications02 engineering and technologyIterative reconstructionhierarchical alternating least squares03 medical and health sciencessimultaneous extraction0302 clinical medicineGroup analysisCore (graph theory)0202 electrical engineering electronic engineering information engineeringTensor decompositionTensorAlgorithmRealization (systems)030217 neurology & neurosurgery
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