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020 _a9783527340972
028 _bStar books
035 _a(CKB)4330000000010734
035 _a(EBL)4708893
035 _a(MiAaPQ)EBC4708893
035 _a(EXLCZ)994330000000010734
040 _aMiAaPQ
_beng
_erda
_epn
_cMiAaPQ
_dPK-SiUMT
050 4 _aQD39.3.M3
_bO88 2017
082 0 _a543.015195
_223
_bOTT-C 2017 12691
100 1 _aOtto, Matthias
_eauthor.
_94748
245 1 0 _aChemometrics :
_bstatistics and computer application in analytical chemistry /
_cMatthias Otto.
250 _aThird edition.
260 _aWeinheim, Germany :
_bWiley-VCH ,
_cc 2017.
264 4 _c©2017
300 _bx, 382 pages ;
_aillustration ;
_c24 cm.
336 _atext
_2rdacontent
337 _acomputer
_2rdamedia
338 _2rdacarrier
500 _aIncludes index.
505 _aTABLE OF CONTENTS List of Abbreviations VII Symbols IX 1 What is Chemometrics? 1 1.1 The Computer-Based Laboratory 2 1.2 Statistics and Data Interpretation 10 1.3 Computer-Based Information Systems/Artificial Intelligence 11 General Reading 12 Questions and Problems 13 2 Basic Statistics 15 2.1 Descriptive Statistics 16 2.2 Statistical Tests 28 2.3 Analysis of Variance 44 General Reading 50 Questions and Problems 52 3 Signal Processing and Time Series Analysis 55 3.1 Signal Processing 56 3.2 Time Series Analysis 83 General Reading 90 Questions and Problems 91 4 Optimization and Experimental Design 93 4.1 Systematic Optimization 94 4.2 Objective Functions and Factors 95 4.3 Experimental Design and Response Surface Methods 102 4.4 Sequential Optimization: Simplex Method 125 General Reading 132 Questions and Problems 133 5 Pattern Recognition and Classification 135 5.1 Preprocessing of Data 137 5.2 Unsupervised Methods 140 5.3 Supervised Methods 184 General Reading 209 Questions and Problems 210 6 Modeling 213 6.1 Univariate Linear Regression 214 6.2 Multiple Linear Regression 231 6.3 Nonlinear Methods 258 General Reading 269 Questions and Problems 271 7 Analytical Databases 273 7.1 Representation of Analytical Information 274 7.2 Library Search 286 7.3 Simulation of Spectra 292 General Reading 294 Questions and Problems 295 8 Knowledge Processing and Soft Computing 297 8.1 Artificial Intelligence and Expert Systems 297 8.2 Neural Networks 306 8.3 Fuzzy Theory 321 8.4 Genetic Algorithms and Other Global Search Strategies 334 General Reading 342 Questions and Problems 344 9 Quality Assurance and Good Laboratory Practice 345 9.1 Validation and Quality Control 346 9.2 Accreditation and Good Laboratory Practice 351 General Reading 352 Questions and Problems 353 Appendix 355 Index 371
520 _aThe third edition of this long-selling introductory textbook and ready reference covers all pertinent topics, from basic statistics via modeling and databases right up to the latest regulatory issues. The experienced and internationally recognized author, Matthias Otto, introduces the statistical-mathematical evaluation of chemical measurements, especially analytical ones, going on to provide a modern approach to signal processing, designing and optimizing experiments, pattern recognition and classification, as well as modeling simple and nonlinear relationships. Analytical databases are equally covered as are applications of multiway analysis, artificial intelligence, fuzzy theory, neural networks, and genetic algorithms. The new edition has 10% new content to cover such recent developments as orthogonal signal correction and new data exchange formats, tree based classification and regression, independent component analysis, ensemble methods and neuro-fuzzy systems. It still retains, however, the proven features from previous editions: worked examples, questions and problems, additional information and brief explanations in the margin.
546 _aEnglish
650 0 _aChemistry
_xMathematics.
_vStatistical methods.
_94749
650 0 _aAnalytical chemistry--Data processing - Chemistry
_xChemistry
_94750
650 0 _aChemistry--Mathematics
_94753
700 _aOtto,Mattias
_94752
776 _z978-3-527-34097-1
856 _3e-Book Chemometrics
_z(Click here to access full-text book)
_uhttps://b-ok.asia/book/2773136/fdd21c
906 _aBOOK
942 _2ddc
_cBK
_eThird edition