000 04365cam a2200517Ii 4500
001 ocn956953629
003 OCoLC
005 20190328114816.0
006 m o d
007 cr cnu|||unuuu
008 160818s2016 ne ob 001 0 eng d
040 _aN$T
_beng
_erda
_epn
_cN$T
_dOPELS
_dEBLCP
_dIDEBK
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_dOCLCF
_dN$T
_dQCL
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_dMERER
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019 _a956998955
_a958096780
_a958393272
_a1066656416
020 _a9780444636447
_q(electronic bk.)
020 _a0444636447
_q(electronic bk.)
020 _z9780444636386
_q(print)
020 _z0444636382
_q(print)
035 _a(OCoLC)956953629
_z(OCoLC)956998955
_z(OCoLC)958096780
_z(OCoLC)958393272
_z(OCoLC)1066656416
050 4 _aQC454.O66
072 7 _aSCI
_x013010
_2bisacsh
082 0 4 _a543/.5
_223
245 0 0 _aResolving spectral mixtures : with applications from ultrafast time-resolved spectroscopy to super-resolution imaging /
_h[electronic resource]
_cedited by Cyril Ruckebusch.
264 1 _aAmsterdam, Netherlands :
_bElsevier,
_c2016.
300 _a1 online resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aData handling in science and technology ;
_vvolume 30
500 _aIncludes index.
588 0 _aOnline resource; title from PDF title page (ScienceDirect, viewed August 24, 2016).
505 0 _aFront Cover; Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Super-Resolution Imaging; Copyright; Contents; Contributors; Preface; Foreword; Chapter 1: Introduction; 1. Introduction; 2. The Spectral Mixture Problem; 3. Book Content and Organization; Chapter 2: Multivariate Curve Resolution-Alternating Least Squares for Spectroscopic Data; 1. MCR: The Concept and the Link with Spectroscopic Data; 2. MCR-ALS: Algorithm and Data Set Configuration; 2.1. MCR-ALS Algorithm: Steps; 2.2. Constraints; 3. MCR-ALS Applied to Process Analysis.
505 8 _a3.1. Encoding Process Information: Sequentiality and Physicochemical Models3.1.1. Sequentiality; 3.1.2. Physicochemical Models; 3.2. Multiset Analysis: Multiexperiment Analysis and Data Fusion; 3.2.1. Multiexperiment Analysis; 3.2.2. Multitechnique Analysis (Data Fusion); 4. MCR-ALS Applied to HSI Analysis; 4.1. Encoding Image Information: The Spatial Dimension; 4.2. Image Multiset Analysis; 4.3. MCR Postprocessing; 5. MCR-ALS and Quantitative Analysis; 5.1. Second-order Calibration; 5.2. First-order Calibration: Correlation Constraint; 6. MCR-ALS and Other Bilinear Decomposition Methods.
505 8 _a1.1. Permutation Ambiguity1.2. Intensity or Scalar Ambiguity; 1.3. Rotation Ambiguities; 2. Evaluation of MCR Ambiguities; 3. Estimation of the Extension of Rotation Ambiguities and of Their MCR Feasible Solutions; 3.1. Optimization Problem and Method; 3.2. Objective Function to Minimize; 3.3. Variables to Optimize; 4. MCR Constraints and Their Implementation; 4.1. Normalization and/or Closure Constraints; 4.2. Nonnegativity Constraints; 4.3. Selectivity and Local Rank Constraints; 4.4. Unimodality; 4.5. Model or Multilinearity Constraints; 4.6. Hard Modeling.
505 8 _a5. Implementation of the MCR-BANDS Method6. Example of Calculation of MCR Feasible Solutions Using the MCR-BANDS Method; 7. Comparison of Solutions Obtained by Different MCR Methods; 8. Comparison of the Ranges of MCR Feasible Solutions Obtained by Different Methods; 9. Conclusions; References; Chapter 5: On the Analysis and Computation of the Area of Feasible Solutions for Two-, Three-, and Four-Component Systems; 1. Introduction; 1.1. Organization of the Chapter; 1.2. Model Data Sets and Experimental Spectral Data; 2. MCR Methods; 2.1. The Singular Value Decomposition.
504 _aIncludes bibliographical references and index.
650 0 _aSpectral imaging.
650 0 _aSpectrum analysis.
650 7 _aSCIENCE
_xChemistry
_xAnalytic.
_2bisacsh
650 7 _aSpectral imaging.
_2fast
_0(OCoLC)fst01910210
650 7 _aSpectrum analysis.
_2fast
_0(OCoLC)fst01129108
655 4 _aElectronic books.
655 0 _aElectronic book.
700 1 _aRuckebusch, Cyril,
_eeditor.
830 0 _aData handling in science and technology ;
_vv. 30.
856 4 0 _3ScienceDirect
_uhttp://www.sciencedirect.com/science/bookseries/09223487/30
999 _c247400
_d247400