Signals processing

Warping, denoising, background correction and signals compression Selected publications:
  1. V. Pravdova, B. Walczak, D.L. Massart, A comparison of two algorithms for warping of analytical signals, Analytica Chimica Acta, 456 (2002) 77-92
  2. A.M. van Nederkassel, M. Daszykowski, P.H.C. Eilers, Y. Vander Heyden, A comparison of three algorithms for chromatograms alignment, Journal of Chromatography A, 1118 (2006) 199-210
  3. W. Wu, M. Daszykowski, B. Walczak, B.C. Sweatman, S.C. Connor, J.N. Haselden, D.J. Crowther, R.W. Gill, M.W. Lutz, Peak alignment of urine NMR spectra using fuzzy warping, Journal of Chemical Information and Modeling, 46 (2006) 863-875
  4. B. Walczak, Wavelets in Chemistry, Elsevier, Amsterdam 2000
  5. C. Perrin, B. Walczak, D.L. Massart, The use of wavelets for signal denoising in capillary electrophoresis, Analytical Chemistry, 73 (2001) 4903-4917
  6. B. Walczak, D.L. Massart, Wavelets - something for analytical chemistry?, Trends in Analytical Chemistry, 16 (1997) 451-463
  7. M. Daszykowski, R. Danielsson, B. Walczak, No-alignment-strategies for exploring a set of two-way data tables obtained from capillary electrophoresis-mass spectrometry, Journal of Chromatography A, 1192 (2008) 157-165
  8. K. Kaczmarek, B. Walczak, S. de Jong, B.G.M. Vandeginste, Feature based fuzzy matching of 2D gel electrophoresis images, Journal of Chemical Information and Computer Sciences, 42 (2002) 1431-1442
  9. K. Kaczmarek, B. Walczak, S. de Jong, B.G.M. Vandeginste, Matching of 2D gel electrophoresis images, Journal of Chemical Information and Computer Sciences, 43 (2003) 978-986
  10. K. Kaczmarek, B. Walczak, S. de Jong, B.G.M. Vandeginste, Baseline reduction in two dimensional gel electrophoresis images, Acta Chromatographica, 15 (2005) 82-96 ->get pdf

Data mining

Clustering methods, projection methods, N-way analysis Selected publications:
  1. I. Stanimirova, B. Walczak, D.L. Massart, V. Simeonov, C.A. Saby, E. Di Crescenzo, STATIS, a 3-way method for data analysis. Application to environmental data, Chemometrics and Intelligent Laboratory Systems, 73 (2004) 219-233
  2. I. Stanimirova, K. Zehl, D.L. Massart, Y. Vander Heyden, J.W. Einax, Chemometric analysis of soil pollution data applying the Tucker N-way method, Analytical and Bioanalytical Chemistry, 385 (2006) 771-773
  3. M. Daszykowski, B. Walczak, D.L. Massart, Projection methods in chemistry, Chemometrics and Intelligent Laboratory Systems, 65 (2003) 97-112
  4. M. Daszykowski, B. Walczak, D.L. Massart, On the optimal partitioning of data with K-means, Growing K-means, Neural Gas and Growing Neural Gas, Journal of Chemical Information and Computer Sciences, 42 (2002) 1378-1389
  5. M. Daszykowski, B. Walczak, D.L. Massart, Looking for Natural Patterns in Data. Part 1: Density Based Approach, Chemometrics and Intelligent Laboratory Systems, 56 (2001) 83-92
  6. M. Daszykowski, B. Walczak, D.L. Massart, Looking for Natural Patterns in Analytical Data. 2. Tracing Local Density with OPTICS, Journal of Chemical Information and Computer Sciences, 42 (2002) 500-507
  7. I. Stanimirova, B. Walczak, D.L. Massart, Multiple Factor Analysis in environmental chemistry, Analytica Chimica Acta, 545 (2005) 1-12

Data modelling

Linear/non-linear calibration and classification Selected publications:
  1. T. Czekaj, W. Wu, B. Walczak, About kernel latent variable approaches and SVM, Journal of Chemometrics, 19 (2005) 341-354
  2. V. Centner, J. Verdu-Andres, B. Walczak, D. Joun-Rimbaud, F. Despagne, O. de Nord, A comparison of multivariate calibration techniques applied to experimental NIR data sets, Applied Spectroscopy, 54 (2000) 608-623
  3. F. Estienne, L. Pasti, V. Centner, B. Walczak, F. Despagne, D. Jouan Rimbaud, O.E. de Noord, D.L. Massart, A comparison of multivariate calibration techniques applied to experimental NIR data sets. Part II: predictive ability under extrapolation conditions, Chemometrics and Intelligent Laboratory Systems, 58 (2001) 195-211
  4. F. Estienne, F. Despagne, B. Walczak, O.E. de Noord, D.L. Massart, A comparison of multivariate calibration techniques applied to experimental NIR data sets. Part III: Robustness against instrumental perturbation conditions, Chemometrics and Intelligent Laboratory Systems, 73 (2004) 207-218
  5. W. Wu, Y. Mallet, B. Walczak, W. Penninckx, D. L. Massart, S. Heuerding, F. Erni, Comparison of regularized discriminant analysis, linear discriminant analysis and quadratic discriminant analysis, applied to NIR data, Analytica Chimica Acta, 326 (1996) 257-265
  6. F. Questier, R. Put, D. Coomans, B. Walczak, Y. Vander Heyden, The use of CART and multivariate regression trees for supervised and unsupervised feature selection, Chemometrics and Intelligent Laboratory Systems, 76 (2005) 45-54
  7. B. Walczak, D.L. Massart, Local modelling with Radial Basis Functions Networks, Chemometrics and Intelligent Laboratory Systems, 51 (2000) 219-238
  8. B. Walczak, D.L. Massart, Application of Radial Basis Functions - Partial Least Squares to non-linear pattern recognition problems: diagnosis of process faults, Analytica Chimica Acta, 331 (1996) 187-193
  9. B. Walczak, D.L. Massart, The Radial Basis Functions - Partial Least Squares approach as a flexible non-linear regression techniques, Analytica Chimica Acta, 331 (1996) 177-185
  10. B. Walczak, W. Wegscheider, Calibration of non-linear analytical systems by a neuro fuzzy approach, Chemometrics and Intelligent Laboratory Systems, 22 (1994) 199-207
  11. B. Walczak, E. Bauer-Wolf, W. Wegscheider, A neuro-fuzzy system for X-ray spectra interpretation, Microchimica Acta, 113 (1994) 153-169

Robust methods

Robust modelling and outlier detection Selected publications:
  1. M. Daszykowski, K. Kaczmarek, Y. Vander Heyden, B. Walczak, Robust statistics in data analysis - a review. Basic concepts, Chemometrics and Intelligent Laboratory Systems, 85 (2007) 203-219
  2. M. Daszykowski, K. Kaczmarek, I. Stanimirova, Y. Vander Heyden, B. Walczak, Robust SIMCA - bounding influence of outliers, Chemometrics and Intelligent Laboratory Systems, 87 (2007) 121-129
  3. I. Stanimirova, B. Walczak, D.L. Massart, V. Simeonov, A comparison between two robust PCA algorithms, Chemometrics and Intelligent Laboratory Systems, 71 (2004) 83-95
  4. V. Pravdova, F. Estienne, B. Walczak, D.L. Massart, Robust version of TUCKER3 model, Chemometrics and Intelligent Laboratory Systems, 59 (2001) 75-88
  5. I. Stanimirova, M. Daszykowski, B. Walczak, Dealing with missing values and outliers in principal component analysis, Talanta, 72 (2007) 172-178
  6. I. Stanimirova, B. Walczak, Classification of data with missing elements and outliers, Talanta, 76 (2008) 602-609
  7. B. Walczak, D.L. Massart, Robust principal components regression as a detection tool for outliers, Chemometrics and Intelligent Laboratory Systems, 27 (1995) 41-54
  8. B. Walczak, D.L. Massart, Multiple outlier detection revisited, Chemometrics and Intelligent Laboratory Systems, 41 (1998) 1-15
  9. B. Walczak, Outlier detection in bilinear calibration, Chemometrics and Intelligent Laboratory Systems, 29 (1995) 63-73
  10. B. Walczak, Outlier detection in multivariate calibration, Chemometrics and Intelligent Laboratory Systems, 28 (1995) 259-272

Missing and censored data

Processing the data with missing elements (and outliers) Selected publications:
  1. B. Walczak, D.L. Massart, Dealing with missing data. Part 1, Chemometrics and Intelligent Laboratory Systems, 58 (2001) 15-17
  2. B. Walczak, D.L. Massart, Dealing with missing data. Part 2, Chemometrics and Intelligent Laboratory Systems, 58 (2001) 29-42
  3. I. Stanimirova, M. Daszykowski, B. Walczak, Dealing with missing values and outliers in principal component analysis, Talanta, 72 (2007) 172-178
  4. I. Stanimirova, B. Walczak, Classification of data with missing elements and outliers, Talanta, 76 (2008) 602-609
  5. I. Stanimirova, S. Serneels, P.J. Van Espen, B. Walczak, How to construct a multiple regression model for data with missing elements and outlying objects, Analytica Chimica Acta, 581 (2007) 324-332
  6. A. SmoliƄski, B. Walczak, Exploratory analysis of chromatographic data sets with missing elements. Initialization of Expectation-Maximization algorithm, Acta Chromatographica, 12 (2002) 30-48 -> get full paper
  7. A. SmoliƄski, B. Walczak, J.W. Einax, Exploratory analysis of data sets with missing elements and outliers, Chemosphere, 49 (2002) 233-245

Areas of applications

Selected publications:
  1. M. Daszykowski, M.S. Wrobel, H. Czarnik-Matusewicz, B. Walczak, Near-infrared reflectance spectroscopy and multivariate calibration techniques applied to model the protein, fiber and fat contents in rapeseed meal, The Analyst, 133 (2008) 1523-1531
  2. M. Daszykowski, B. Walczak, Use and abuse of chemometrics in chromatography, Trends in Analytical Chemistry, 25 (2006) 1081-1096
  3. R. Put, M. Daszykowski, T. Baczek, Y. Vander Heyden, Retention Prediction of Peptides Based on Uninformative Variable Elimination by Partial Least Squares, Journal of Proteome Research, 5 (2006) 1618-1625
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