[go: up one dir, main page]

Jiang et al., 2004 - Google Patents

Principles and methodologies in self-modeling curve resolution

Jiang et al., 2004

Document ID
4448886051202618413
Author
Jiang J
Liang Y
Ozaki Y
Publication year
Publication venue
Chemometrics and intelligent laboratory systems

External Links

Snippet

This review paper aims at examining the recent developments in self-modeling curve resolution (SMCR). Particular emphasis is put on the progress in methodologies for SMCR. A historical review is described first, and the principle of SMCR is explained next. Then, a …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6217—Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/86—Signal analysis
    • G01N30/8624—Detection of slopes or peaks; baseline correction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N30/00—Investigating or analysing materials by separation into components using adsorption, absorption or similar phenomena or using ion-exchange, e.g. chromatography or field flow fractionation
    • G01N30/02—Column chromatography
    • G01N30/86—Signal analysis
    • G01N30/8675—Evaluation, i.e. decoding of the signal into analytical information
    • G01N30/8682—Group type analysis, e.g. of components having structural properties in common
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colour
    • G01J3/28—Investigating the spectrum
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00496—Recognising patterns in signals and combinations thereof
    • G06K9/00503—Preprocessing, e.g. filtering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED, VISIBLE OR ULTRA-VIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
    • G01J3/00—Spectrometry; Spectrophotometry; Monochromators; Measuring colour
    • G01J3/12—Generating the spectrum; Monochromators
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods

Similar Documents

Publication Publication Date Title
Jiang et al. Principles and methodologies in self-modeling curve resolution
Jiang et al. Self-modeling curve resolution (SMCR): principles, techniques, and applications
Sanchez et al. Tensorial calibration: II. Second‐order calibration
Sanchez et al. Tensorial resolution: a direct trilinear decomposition
JP3045729B2 (en) Component spectrum estimation method
Kriesten et al. Identification of unknown pure component spectra by indirect hard modeling
Lorber et al. The effect of interferences and calbiration design on accuracy: Implications for sensor and sample selection
Tauler et al. Selectivity, local rank, three‐way data analysis and ambiguity in multivariate curve resolution
Kermit et al. Independent component analysis applied on gas sensor array measurement data
Smilde et al. Theory of medium‐rank second‐order calibration with restricted‐Tucker models
Abdollahi et al. Uniqueness and rotation ambiguities in multivariate curve resolution methods
US6341257B1 (en) Hybrid least squares multivariate spectral analysis methods
Brown Chemical systems under indirect observation: Latent properties and chemometrics
Tauler Application of non-linear optimization methods to the estimation of multivariate curve resolution solutions and of their feasible band boundaries in the investigation of two chemical and environmental simulated data sets
Grande et al. Use of convexity for finding pure variables in two-way data from mixtures
Dadashi et al. Maximum likelihood principal component analysis as initial projection step in multivariate curve resolution analysis of noisy data
US10557792B2 (en) Spectral modeling for complex absorption spectrum interpretation
Tavakkoli et al. Soft-trilinear constraints for improved quantitation in multivariate curve resolution
Shen et al. Determination of chemical rank of two-way data from mixtures using subspace comparisons
Armstrong et al. PARAFAC2× N: Coupled decomposition of multi-modal data with drift in N modes
Faber et al. Generalized rank annihilation method. II: Bias and variance in the estimated eigenvalues
Biagioni et al. Orthogonal projection to latent structures solution properties for chemometrics and systems biology data
Lakeh et al. Known-value constraint in multivariate curve resolution
Tan et al. Mutual information-induced interval selection combined with kernel partial least squares for near-infrared spectral calibration
Jiang et al. On simplex-based method for self-modeling curve resolution of two-way data