Pattern Recognition

REFERENCES

• Jurs , P. C. , Kowalski , B. R. , Isenhour , T. L. and Reilley , C. N. 1969 . Computerized learning machines applied to chemical problems: convergence rate and predictive ability of adaptive binary pattern classifiers . Analytical Chemistry , 41 : 690 – 695 . [CSA]
   Web of Science ®Google Scholar
• Jurs , P. C. , Kowalski , B. R. , Isenhour , T. L. and Reilley , C. N. 1969 . Computerized learning machines applied to chemical problems: multicategory pattern classification by least squares . Analytical Chemistry , 41 : 695 – 700 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Jurs , P. C. , Kowalski , B. R. , Isenhour , T. L. and Reilley , C. N. 1970 . Computerized learning machines applied to chemical problems: molecular structure parameters from low resolution mass spectrometry . Analytical Chemistry , 42 : 1387 – 1394 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Jurs , P. C. 1971 . Machine intelligence applied to chemical systems: prediction and reliability improvement in classification of low resolution mass spectrometry data . Analytical Chemistry , 43 : 22 – 26 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Brodnjak-Voncina , D. , Kodba , Z. C. and Novic , M. 2005 . Multivariate data analysis in classification of vegetable oils characterized by the content of fatty acids . Chemometrics and Intelligent Laboratory Systems , 75 : 31 – 43 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Johnson , C. A. , Topoff , H. , Vander Meer , R. K. and Lavine , B. K. 2005 . “Do these eggs smell funny to you? Egg discrimination by formica hosts of the slave-making ant, Polyergus breviceps (Hymenoptera: Formicidae) . Behavior Ecology and Sociobiology , 57 : 245 – 255 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Simo , C. , Martin-Alvarez , P. , Barbas , C. and Cifuentes , A. 2004 . Application of stepwise discriminant analysis to classify commercial orange juices using chiral micellar electrokinetic chromatography-laser induced fluorescence data of amino acids . Electrophoresis , 25 : 2885 – 2891 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Johnson , C. R. , Topoff , H. , Vander Meer , R. K. and Lavine , B. K. 2002 . Queens ripe for the killing: When a host queen becomes the target of aggression by the slave-maker ant queen, Polyergus breviceps . Animal Behavior , 64 : 807 – 815 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Johnson , C. , Vander Meer , R. K. and Lavine , B. K. 2001 . Changes in the cuticular hydrocarbon profile of the slave-maker ant queen, polyergus breviceps, after killing a formica queen . Journal of Chemical Ecology , 27 : 1787 – 1804 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Lavine , B. K. , Brzozowski , D. , Ritter , J. , Moores , A. J. and Mayfield , H. T. 2001 . Fuel Spill identification by selective fractionation prior to gas chromatography I. Water soluble components . Journal of Chromatographic Science , 39 : 501 – 506 . [INFOTRIEVE] [CSA]
   PubMedGoogle Scholar
• White , R. L. , Wentzell , P. D. , Beasy , M. A. , Clark , D. S. and Grund , D. W. 1993 . Taxonomy of Amanita mushrooms by pattern recognition of amino acid chromatographic data . Analytica Chimica Acta , 277 : 333 – 346 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Clark , H. A. and Jurs , P. C. 1979 . Classification of crude oil gas chromatograms by pattern recognition techniques . Analytical Chemistry , 51 : 616 – 623 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Gemperline , P. J. and Boyer , N. R. 1995 . Classification of near-infrared spectra using wavelength distances: comparison to the Mahalanobis distance and residual variance methods . Analytical Chemistry , 67 : 160 – 166 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Shah , N. K. and Gemperline , P. J. 1990 . Combination of the Mahalanobis distance and residual variance pattern recognition techniques for classification of near-infrared spectra . Analytical Chemistry , 62 : 465 – 470 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Gemperline , P. J. , Webber , L. D. and Cox , F. O. 1989 . Raw materials testing using soft independent modeling of class analogy analysis of near-infrared reflectance spectra . Analytical Chemistry , 61 ( 2 ) : 138 – 144 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Jurs , P. C. 1986 . Pattern recognition used to investigate multivariate data in analytical chemistry . Science , 232 : 1219 – 1224 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Jurs , P. C. , Bakken , G. A. and McClelland , H. E. 2000 . Computational methods for the analysis of chemical sensor array data from volatile analytes . Chemical Reviews , 100 ( 7 ) : 2649 – 2678 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Massart , D. L. and Kaufman , L. 1983 . The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis , New York : John Wiley & Sons .
   Google Scholar
• Brereton , R. G. , ed. 1992 . Multivariate Pattern Recognition in Chemometrics , Amsterdam : Elsevier .
   Google Scholar
• McLachlan , G. J. 1992 . Discriminant Analysis and Statistical Pattern Recognition , New York : John Wiley & Sons .
   Google Scholar
• Ripley , B. D. 1996 . Pattern Recognition and Neural Networks , Cambridge : University Press .
   Google Scholar
• Beebe , K. R. , Pell , R. J. and Seasholtz , M. B. 1998 . Chemometrics: A Practical Guide , New York : John Wiley & Sons .
   Google Scholar
• Siddiqui , K. J. and Eastwood , D. September 1999 . Pattern Recognition, Chemometrics, and Imaging for Optical Environmental Monitoring , SPIE Proceedings Volume 3854 , September ,
   Google Scholar
• Duda , R. , Hart , P. E. and Stork , D. G. 2000 . Pattern Classification and Scene Analysis, , 2nd Ed. , New York : Wiley-Interscience .
   Google Scholar
• Jackson , J. E. 1991 . A User's Guide to Principal Component Analysis , New York : John Wiley & Sons .
   Google Scholar
• Jolliffe , I. T. 1986 . Principal Component Analysis , New York : Springer-Verlag .
   Google Scholar
• Wang , C. P. and Isenhour , T. L. 1987 . Infrared library search on principal component analyzed Fourier transform absorption spectra . Analytical Chemistry , 41 : 185 – 194 . [CSA]
   Google Scholar
• Bjerga , J. M. and Small , G. W. 1990 . Automated selection of library subsets for infrared searching . Analytical Chemistry , 62 : 226 – 233 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Small , G. W. 1987 . Automated spectral interpretation . Analytical Chemistry , 59 : 535A – 545A . [CSA]
   Web of Science ®Google Scholar
• Luinge , H. J. 1990 . Automated interpretation of vibrational spectra . Vibrational Spectroscopy , 1 : 3 – 18 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Huang , J. and Esbensen , K. H. 2000 . Applications of angle measure technique (AMT) in image analysis Part I. A new methodology for in situ powder characterization . Chemolab , 54 : 1 – 19 . [CSA]
   Google Scholar
• Huang , J. and Esbensen , K. H. 2001 . Applications of AMT (angle measure technique) in image analysis Part II: Prediction of powder functional properties and mixing components . Chemometrics and Intelligent Laboratory Systems , 57 : 37 – 56 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Bright , D. Measurement of chemical components using scatter diagrams with principal component analysis . Microbeam Anal. Proc. Annu. Conf. Microbeam Anal Soc. 29th . Edited by: Etz , E. pp. 403 – 404 . New York : VCH .
   Google Scholar
• Eliasson , C. , Loren , A. , Engelbrektsson , J. , Josefson , M. , Abrahamsson , J. and Abrahamsson , K. 2005 . Surface-enhanced Raman scattering of single living lymphocytes with multivariate evaluation . Spectrochimica Acta. Part A: Molecular and Biomolecular Spectroscopy , 61A : 755 – 760 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Ben-Amotz , D. and Zhang , D. 2002 . Removal of cosmic spikes from hyper-spectral images using a hybrid upper bound spectrum method . Applied Spectroscopy , 56 : 91 – 98 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Stellman , C. M. , Booksh , K. S. , Muroski , A. R. , Nelson , M. P. and Myrick , M. L. 1998 . Principal component mapping applied to Raman microspectroscopy of fiber-reinforced polymer composites . Science and Engineering Composite Materials , 7 : 51 – 80 . [CSA]
   Google Scholar
• Sasic , S. , Clark , D. , Mitchell , J. C. and Snowden , M. 2004 . A comparison of Raman chemical images produced by univariate and multivariate data processing—A simulation with an example from pharmaceutical practice . Analyst , 129 : 1001 – 1007 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Zhang , L. , Henson , M. J. and Sekulic , S. 2005 . Multivariate data analysis for Raman imaging of a model pharmaceutical tablet . Analytica Chimica Acta , 545 : 262 – 278 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Baronti , S. , Casini , A. , Lott , F. and Porciani , S. 1997 . Principal component analysis of visible and near infrared multispectral images of works of art . Chemometrics and Intelligent Laboratory Systems , 39 : 103 – 114 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• van den Broek , W. H. A. M. , Wienke , D. , Melssen , W. J. , Feldhoff , R. , Huth-Fehre , T. , Kantimm , T. and Buydens , L. M. C. 1997 . Application of a spectroscopic infrared focal plane array sensor for on-line identification of plastic waste . Applied Spectroscopy , 51 : 856 – 865 . [CROSSREF] [CSA]
   Google Scholar
• Karasinski , J. , Andreescu , S. , Sadik , O. A. , Lavine , B. and Vora , M. N. 2005 . Multiarray sensors with pattern recognition for the detection, classification, and differentiation of bacteria at subspecies and strain levels . Analytical Chemistry , 77 : 7941 – 7949 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Lavine , B. K. , Davidson , C. E. and Rayens , W. T. 2004 . Machine learning based pattern recognition applied to microarray data . Combinatorial Chemistry and High Throughput Screening , 7 : 115 – 131 . [INFOTRIEVE] [CSA]
   PubMedGoogle Scholar
• Lavine , B. K. and Vora , M. 2005 . Identification of Africanized honeybees . Journal of Chromatography A , 1096 : 69 – 75 . [INFOTRIEVE] [CSA]
   PubMed Web of Science ®Google Scholar
• Lavine , B. K. , Davidson , C. E. and Moores , A. J. 2002 . Genetic algorithms for spectral pattern recognition . Vibrational Spectroscopy , 28 : 83 – 95 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Lavine , B. K. , Vesanen , A. , Brzozowski , D. M. and Mayfield , H. T. 2001 . Authentication of fuel standards using gas chromatography/pattern recognition techniques . Analytical Letters , 34 : 281 – 294 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Lavine , B. K. , Davidson , C. E. , Moores , A. J. and Griffiths , P. R. 2001 . Raman spectroscopy and genetic algorithms for the classification of wood types . Applied Spectroscopy , 55 : 960 – 966 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Lavine , B. K. , Brzozowski , D. , Moores , A. J. , Davidson , C. E. and Mayfield , H. T. 2001 . Genetic algorithm for fuel spill identification . Analytica Chimica Acta , 437 : 233 – 246 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Lavine , B. K. , Ritter , J. , Moores , A. J. , Wilson , M. , Faruque , A. and Mayfield , H. T. 2000 . Source identification of underground fuel spills by solid phase micro-extraction/high-resolution gas chromatography/genetic algorithms . Analytical Chemistry , 72 : 423 – 431 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Ramos , L. S. 1994 . Characterization of mycobacteria species by HPLC and pattern recognition . Journal of Chromatographic Science , 32 : 219 – 227 . [INFOTRIEVE] [CSA]
   PubMedGoogle Scholar
• Gidman , E. , Goodacre , R. , Emmet , B. , Smith , R. A. and Gwynn-Jones , D. 2003 . Investigating plant-plant interference by metabolic fingerprinting . Phytochemistry , 63 : 705 – 710 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Jarvis , R. M. and Goodacre , R. 2004 . Discrimination of bacteria using surface-enhanced Raman spectroscopy . Analytical Chemistry , 76 : 40 – 47 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Zheng , C. and Suslick , K. S. 2005 . A colorometric sensor array for organics in water . Journal of the American Chemical Society , 127 : 11548 – 11549 . [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Sepcic , K. , Josowicz , M. , Janata , J. and Selby , T. 2004 . Diagnosis of used engine oil based on gas phase analysis . Analyst , 129 : 1070 – 1075 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Masila , M. , Sargent , A. and Sadik , O. A. 1998 . Pattern recognition studies of halogenated organic compounds using conducting polymer sensor arrays . Electroanalysis , 10 : 312 – 320 . [CROSSREF] [CSA]
   Google Scholar
• Nello Cristianini and John Shawe-Taylor . 2000 . An Introduction to Support Vector Machines and Other Kernel-based Learning Method , UK : Cambridge University Press .
   Google Scholar
• Kecman , Vojislav . 2001 . Learning and Soft Computing: Support Vector Machines, Neural Networks, and Fuzzy Logic Models (Complex Adaptive Systems) , Cambridge, MA : MIT Press .
   Google Scholar
• Blank , T. B. and Brown , S. D. 1993 . Nonlinear multivariate mapping of chemical data using feed-forward neural networks . Analytical Chemistry , 65 : 3081 – 3089 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Blank , T. B. and Brown , S. D. 1993 . Data processing using neural networks . Analytica Chimica Acta , 277 : 273 – 287 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Brudzewski , K. , Kesik , A. , Kolodziejczyk , K. , Zborowska , U. and Ulaczyk , J. 2006 . Gasoline quality prediction using gas chromatography and FTIR spectroscopy: An artificial intelligence approach . Fuel , 85 : 553 – 558 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Zomer , S. , Brereton , R. G. , Carter , J. F. and Eckers , C. 2004 . Support vector machines for the discrimination of analytical chemical data: Application to the determination of tablet production by pyrolysis gas chromatography-mass spectrometry . Analyst , 129 : 175 – 181 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Vapnik , V. 1995 . The Nature of Statistical Learning Theory , NY : Springer-Verlag .
   Google Scholar
• Sadik , O. , Land , W. H. , Wanekaya , A. , Uematsu , M. , Embrechts , M. , Wong , L. , Leibensperger , D. and Volykin , A. 2002 . Detection of classification of organophosphate nerve agent simulants using support vector machines with multiarray sensors . Journal of Chemical Information and Computer Sciences , 44 : 499 – 507 . [CROSSREF] [CSA]
   Google Scholar
• Vohradsky , J. 1997 . Adaptive classification of two-dimensional gel electrophoresis spot patterns by neural networks and cluster analysis . Electrophoresis , 18 : 2749 – 2754 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Dolmatova , L. , Ruckerbusch , C. , Dupuy , N. , Huvenne , J. P. and Legrand , P. 1998 . Identification of modified starches using infrared spectroscopy and artificial neural network processing . Applied Spetroscopy , 52 : 329 – 338 . [CSA]
   Web of Science ®Google Scholar
• Cai , C. and deHarrington , P. 1999 . Prediction of substructure and toxicity of pesticides with temperature constrained cascade correlation network from low-resolution mass spectra . Analytical Chemistry , 71 : 4134 – 4141 . [INFOTRIEVE] [CSA]
   PubMed Web of Science ®Google Scholar
• Walker , C. G. H. 1996 . Analysis of multispectral microscope images using neural networks . Surface and Interface Analysis , 24 : 173 – 180 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Dettmar , H. P. , Barbour , G. S. , Blackwell , K. T. , Vogl , T. P. , Alkon , D. L. , Fry , F. S. , Totayh , J. E. and Chambers , T. L. 1996 . Orange juice classification with a biologically based neural network . Journal of Combinatorial Chemistry , 20 : 261 – 266 . [CSA]
   Google Scholar
• Jensen , K. , Tygsen , T. , Kesmir , C. , Skovgaard , I. M. and Sondergaard , I. 1997 . Classification of potato varieties using isoelectrophoretic focusing patterns, neural nets and statistical methods . Journal of Agriculture and Food Chemistry , 45 : 158 – 161 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Sun , L. X. , Danzer , K. and Thiel , G. 1997 . Classification of wine samples by means of artificial neural networks and discriminant analytical methods . Fresenius Journal of Analytical Chemistry , 359 : 143 – 149 . [CROSSREF] [CSA]
   Google Scholar
• Wold , S. 1976 . Pattern recognition by means of disjoint principal component models . Pattern Recognition , 8 : 127 – 139 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Frank , I. and Friedman , J. 1989 . Classification: Oldtimers and newcomers . Journal of Chemometrics , 3 : 463 – 475 . [CROSSREF] [CSA]
   Google Scholar
• Burl , M. C. , Sisk , B. C. , Vaid , T. P. and Lewis , N. S. 2002 . Classification performance of carbon black polymer composite vapor detector arrays as a function of array size and detector composition . Sensors and Actuators B , B87 : 130 – 149 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Stetter , J. R. , Findlay , M. W. , Schroeder , K. M. , Yue , C. and Penrose , W. R. 1993 . Quality classification of grain using a sensor array and pattern recognition . Analytica Chimica Acta , 248 : 1 – 11 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Lavine , B. K. , Faruque , A. , Kroman , P. and Mayfield , H. T. 1995 . Source identification of fuel spills by pattern recognition analysis of high speed gas chromatograms . Analytical Chemistry , 67 : 3846 – 3852 . [CROSSREF] [CSA]
   Web of Science ®Google Scholar
• Chau , F. , Liang , Y. , Gao , J. and Shao , X. 2004 . Chemometrics—From Basics to Wavelet Transform , New York : Wiley Interscience .
   Google Scholar
• Pino , J. A. , McMurry , J. E. , Jurs , P. C. , Lavine , B. K. and Harper , A. M. 1985 . Applications of pyrolysis/gas chromatography/pattern recognition to the detection of CF heterozygotes . Analytical Chemistry , 57 : 295 – 302 . [INFOTRIEVE] [CROSSREF] [CSA]
   PubMed Web of Science ®Google Scholar
• Lavine , B. K. , Mayfield , H. and Stine , A. 1992 . Application of pattern recognition techniques to problems in advanced pollution monitoring . Process and Quality Control , 2 : 347 – 355 . [CSA]
   Google Scholar