61. M. Pawlak and S. Liao, 2001. "On the recovery of a function on a circular domain". IEEE Tran. Information Theory, to appear (accepted September 2001).

60. M. Pawlak , 2001. "Signal sampling and recovery under dependent noise". Journal on Sampling and Theory and Image Processing, to appear (accepted July, 2001).

59.A. Kozek M. Pawlak , 2001. "Universal consistency of kernel nonparametric M-estimators". Statistics and Probability Letters, to appear (accepted September 2001).

58. M. Pawlak and E. Rafajlowicz, 2001. "Jump preserving signal reconstruction using vertical weighting of samples". Journal of Nonlinear Analysis, vol.47, pp. 327-338.

57. M. Pawlak and W. Schmid, "On the distributional properties of ARCH models".Journal of Time Series, to appear.

56. M. Pawlak and U.Stadtmuller, 2001. "Statistical aspects of sampling for noisy and grouped data". In Modern Sampling Theory: Mathematics and Applications ed. J.Benedetto and J.Ferreira, Birkhauser, pp.317-342.

55. M. Pawlak and E. Rafajlowicz, 2000. "Vertically weighted re gression: a tool for constructing control cards". Statistical Archives, vol.84, pp. 367-388.

54. M. Pawlak and D. Siu, 1998, "Classification with noisy features", in Advances in Pattern Recognition, eds. A. Amin, D. Dori, P. Pudil and H. Freeman. Lecture Notes in Computer Science, vol. 1451, pp. 845--852.

53. M. Pawlak and U. Stadtmüller, 1999, "Statistical aspects of sampling for noisy and grouped data", Modern Sampling Theory: Mathematics and Applications, ed. J. Benedetto and J. Ferreira, Birkhauser, to appear.

52. M. Pawlak, 1998, "Nonparametric estimation of the G/G/1 queueing system", Advances in Matrix Analytic Methods for Stochastic Models, ed. A. Alfa and S. Chakravarthy, Notable Publications, pp. 279--294.

51. M. Pawlak and U. Stadtm\xfcller, 1999, "Kernel density estimation with generalized binning", Scandinavian Journal of Statistics, vol. 26, pp.1-23.

50. X. Liao and M. Pawlak, 1998, On the accuracy of Zernike moments for image analysis", IEEE Tr. Pattern Analysis and Machine Intelligence, vol. 20, pp.1358-1364.

49. M. Pawlak and Z. Hasiewicz, 1998, "Nonlinear system identification by the Haar multiresolution analysis", IEEE Trans. Circuits and Systems, vol. 45, pp. 945--961.

48. X. Liao and M. Pawlak, 1998, "A study of Zernike moment computing" Lecture Notes in Computer Science, vol. 1351, pp. 394--401, edited by R. Chin and T.C. Pong Springer-Verlag, New York.

47. E. Rafajlowicz and M. Pawlak, 1997, "On function recovery by neural networks based on orthogonal expansions", Nonlinear Analysis Theory, Methods \& Applications, vol. 30, pp. 1343--1354.

46. A. Krzyzak, and E. Rafajlowicz and M. Pawlak, 1997, "Moving average algorithms for band-limited signal recovery", IEEE Trans. Signal Processing, vol. 45, pp. 2967--2976.

45. M. Pawlak and U. Stadtm\xfcller, 1997, ``Kernel density estimators from quantized data'', Nonlinear Analysis Theory, Methods \& Applications, vol. 30, pp. 3553--3559.

44. M. Pawlak and U. Stadtm\xfcler, 1997, ``Nonparametric estimation of a class of smooth functions'', Journal of Nonparametric Statistics, vol. 8, pp. 149--183.

43. M. Pawlak and U. Stadtm\xfcller, 1997, ``Kernel regression estimators for signal recovery'', Statistics and Probability Letters, vol. 31, pp. 185--198.

42. M. Pawlak and U. Stadtm\xfcller, 1996, ``Recovering band-limited signals under noise'', IEEE Trans. Inf. Theory, vol. 42, pp. 1425--1438.

41. M. Pawlak, E. Rafajlowicz and A. Krzyzak, 1996, ``Double exponential weighting algorithm for band-limited signals restoration'', IEEE Trans. Signal Processing, vol. 44, pp. 538--545.

40. X. Liao and M. Pawlak, 1996, ``On image analysis by moments'', IEEE Trans. Pattern Analysis Machine Intelligencei, vol. 18, pp. 254--266.

39. X. Liao and M. Pawlak, 1996, ``Chinese character recognition via orthogonal moments'', Lecture Notes in Computer Science, edited by J.Y. Chouinard, P. Fortier, T.A. Gulliver, vol. 1133, pp. 296--308, Springer-Verlag, New York.

38. M. Pawlak, 1995, ``Discontinuity estimation in nonparametric regression via orthogonal series'', in Computing Science and Statistics, edited by J. Sall and A. Lehman, vol. 26, pp. 252--256, Interface Foundation of North America.

37. M. Pawlak and X. Liao, 1994, ``On the digital approximation of moment descriptors'', Machnine Graphics \& Vision, vol. 3, pp. 61--68.

36. W. Greblicki and M. Pawlak, 1994, ``Nonparametric recovering of nonlinearities in systems with the help of Laguerre polynomials'', Control-Theory and Advanced Technology (Japan), vol. 10, No. 4, pp. 771--791.

35. G. Lugosi and M. Pawlak , 1994, ``On the posterior probability estimate of the error rate of nonparametric classification rules'', IEEE Trans. Information Theory, vol. 40, No. 2, pp. 475--481.

34. M. Pawlak and E.\ Rafajlowicz, 1994, ``On restoring band-limited signals'', IEEE Trans. Information Theory, vol. 40, No. 5, pp. 1490--1503.

33. W. Greblicki and M. Pawlak, 1994, ``Dynamic System Identification with Order Statistics'', IEEE Trans. Information Theory, vol. 40, No. 5, pp. 1475--1489.

32. W. Greblicki and M. Pawlak, 1994, ``Nonparametric identification of a cascade nonlinear system'', International Journal of Systems Science, vol. 25, No. 1, pp. 129--153 .

31. M. Pawlak, 1993, ``Kernel classification rules from missing data'', IEEE Trans. Information Theory , vol. 39, pp. 979--988.

30. M. Pawlak, 1992, ``On the reconstruction aspects of moment descriptors'', IEEE Trans. Information Theory, vol. 38, pp. 1698--1709.

29. W. Greblicki and M. Pawlak, 1992, ``Nonparametric identification of a particular nonlinear time series system'', IEEE Trans. on Signal Processing, vol. 40, pp. 985--989.

28. M. Pawlak and W. Greblicki, 1991, ``Nonparametric estimation of a class of nonlinear time series models'', invited paper for the NATO Advanced Study Institute, Nonparametric Functional Estimation and Related Topics, ed. G.G.\ Roussas, Kluwer Academic Publisher.

27. W. Greblicki and M. Pawlak, 1991, ``Nonparametric identification of a cascade nonlinear time series system'', Signal Processing, vol. 22, pp. 61--75.

26. M. Pawlak, 1991, ``On the series expansion approach to the identification of Hammerstein systems'', IEEE Trans. Autom. Control, vol. 36, pp. 763--767.

25. M. Pawlak, 1991, ``On the almost everywhere properties of the kernel regression estimate'', Annals of the Institute of Statistical Mathematics, vol. 43, pp. 311--326.

24. W. Greblicki and M. Pawlak, 1989, ``Nonparametric identification of Hammerstein systems'', IEEE Trans. Information Theory, vol. 35, pp. 409--418.

23. W. Greblicki and M. Pawlak, 1989, ``Recursive nonparametric identification of Hammerstein systems'', Journal of Franklin Institute, vol. 326, pp. 461--481.

22. M. Pawlak, 1989, `` Note on the asymptotic properties of smoothed estimators of the classification error-rate'', Pattern Recognition, vol. 22, p. 221.

21. M. Pawlak, 1988, ``On the asymptotic properties of smoothed estimators of the classification error-rate'', Pattern Recognition, vol. 21, pp. 515--524.

20. M. Pawlak, 1987, Contribution to the discussion of the paper ``What is Projection Pursuit'', by M.C. Jones and R. Sibson, Journal Royal Statistical Society A, vol. 150, pp. 1--36; the contribution pp. 31--32.

19. W. Greblicki and M. Pawlak, 1987, ``Necessary and sufficient conditions for Bayes risk consistency of recursive kernel classification rule'', IEEE Trans. Information Theory, vol. IT-33, pp. 408--412.

18. W. Greblicki and M. Pawlak, 1987, ``Hammerstein system identification by non-parametric regression estimation'', International Journal of Control}, vol. 45, pp. 343--354.

17. W. Greblicki and M. Pawlak, 1987, ``Necessary and sufficient pointwise consistency conditions for recursive kernel regression estimate'', Journal of Multivariate Analysis, vol. 23, pp. 67--76.

16. A. Krzyzak and M. Pawlak, 1987, ``The pointwise rate of convergence of the kernel regression estimate'', Journal of Statistical Planning and Inference, vol. 16, pp. 159--166.

15. M. Pawlak, 1986, ``On nonparametric estimation of a functional of a probability density'', IEEE Trans. Information Theory, vol. 32, no. 1, pp. 73--84.

14. W. Greblicki and M. Pawlak, 1986, ``Nonparametric identification of discrete Hammerstein Systems'', IEEE Trans. Automatic Control, vol. 31, no. 1, pp. 74--77.

13. W. Greblicki and M. Pawlak, 1985, ``Fourier and Hermite series regression estimates'', Annals of the Institute of Statistical Mathematics, vol. 37, pp. 443--454.

12. W. Greblicki and M. Pawlak, 1985, ``Pointwise consistency of the Hermite series density estimate'', Statistics and Probability Letters, vol. 3, pp. 65--69.

11. W. Greblicki and M. Pawlak, 1985, Contribution to the discussion of the paper, ``Some Aspects of the Spline Smoothing Approach to Nonparametric Regression Curve Fitting`` by B.W. Silverman, Journal Royal Statistical Society, vol. 47, pp. 1--52; the contribution pp. 36--37.

10. W. Greblicki, A. Krzyzak, and M. Pawlak, 1984, ``Distribution free pointwise consistency of kernel regression estimate'', Annals of Statistics, vol. 12, pp. 1570--1575.

9. W. Greblicki and M. Pawlak, 1984, ``Hermite series estimate of a probability density and its derivatives'', Journal of Multivariate Analysis, vol. 15, pp. 174--182.

8. A. Krzyzak and M. Pawlak, 1984, ``Distribution free consistency of nonparametric kernel regression estimate and classification'', IEEE Trans. Information Theory, vol. 30, pp. 78--81 .

7. A. Krzyzak and M. Pawlak, 1984, ``Almost everywhere convergence of recursive regression estimate and classification'', IEEE Trans.\ Information Theory, vol. 30, pp. 91--93.

6. W. Greblicki and M. Pawlak, 1983, ``Almost sure convergence of classifying procedure using Hermite series density estimate'', Pattern Recognition Letters, vol. 2, pp. 13--17.

5. A. Krzyzak and M. Pawlak, 1983, ``Universal consistency results for Wolverton-Wagner regression function estimates with applications in discrimination'', Problems of Control and Information Theory, vol. 12, pp. 33--42.

4. A. Krzyzak and M. Pawlak, 1982, ``Almost everywhere convergence of recursive kernel regression function estimates'', Probability and Statistical Inference, ed. W. Wertz, Reidel Publishing Company, pp. 191--209.

3. A. Krzyzak and M. Pawlak, 1982, ``Estimation of multivariate density by orthogonal series'', Probability and Statistical Inference, ed. W. Wertz, Reidel Publishing Company, , pp. 211--221.

2. W. Greblicki and M. Pawlak, 1982, ``A classification procedure using the Multiple Fourier Series'', Information Sciences, vol. 26, pp. 115--126.

1. W. Greblicki and M. Pawlak, 1981, ``Classification using the Fourier Series Estimate of Multivariate Density Functions'', IEEE Trans. Systems, Man, and Cybernetics, vol. 11, pp. 726--730.