Fuzzy theory, methods, and applications in nonlinear signal processing

Intelligent Systems: Technology and Applications, Six Volume Set

Volumn , Issue , 2002, Pages III-49-III-101

  Barner, Kenneth E ^a  

^a UNIVERSITY OF DELAWARE   (United States)

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EID: 33745599730     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Chapter

References (58)

1. Arce, G.R., Kim, Y.T., and Barner, K.E., Order-statistic filtering and smoothing of time series:Part 1, in Order Statistics and their Applications (Rao C.R. and Balakrishnan, N., Eds.), vol. 16 of Handbook of Statistics, pp. 525-554, Amsterdam, The Netherlands: Elsevier Science, 1998.
2. Barner K.E. and Arce, G.R., Order-statistic filtering and smoothing of time series: Part 2, in Order Statistics and their Applications (Rao C.R. and Balakrishnan, N., Eds.), vol. 16 of Handbook of Statistics, pp. 555-602, Amsterdam, The Netherlands: Elsevier Science, 1998.
3. Arce G.R. and Barner, K.E., Nonlinear signals and systems, in Encyclopedia of Electrical and Electronics Engineering (Webster, J.G., Ed.), pp. 612-630, New York: John Wiley & Sons, 1998.
4. Barner K.E. and Hardie, R.C., Spatial-rank order selection filters, in Nonlinear Image Processing. (Mitra S.K. and Sicuranza, G., Eds.), San Diego, CA: Academic Press, 2001.
5. Edgeworth, F.Y., A new method of reducing observations relating to several quantities, Phil. Mag. (Fifth Series), vol. 24, 1887.
6. Barner, K.E., Flaig, A., and Arce, G.R., Fuzzy time-rank relations and order statistics, IEEE Signal Proc. Lett., 5, 252-255, Oct. 1998.
7. Barner, K.E., Nie, Y., and An, W., Fuzzy ordering theory and its use in filter generalizations, EURASIP J. Appl. Signal Proc.-Special Issue on Nonlinear Signal and Image Proc., Dec. 2001.
8. Flaig, A., Barner, K.E., and Arce, G.R., Fuzzy ranking: theory and applications, Signal Proc. Special Issue on Fuzzy Processing, 80, 1017-1036, June 2000.
9. Flaig, A., Arce, G.R., and Barner, K.E., Affine order statistic filters: a data-adaptive filtering framework for nonstationary signals, IEEE Trans. Signal Proc., 46, 2101-2112, 1998.
10. Lee, Y.H. and Kassam, S.A., Generalized median filtering and related nonlinear filtering techniques, IEEE Trans. Acoustics, Speech, and Signal Proc., 33, 672-683, June 1985.
11. Cha I. and Kassam, S.A., Channel equalization using adaptive complex radial basis function networks, IEEE J. Select Areas of Communications, 13, 964-975, Jan. 1995.
12. Cha I. and Kassam, S.A., RBFN restoration of nonlinearly degraded images, IEEE Trans. Image Proc., 5, 122-131, June 1996.
13. Haykin, S., Adaptive Filter Theory. New Jersey: Prentice-Hall, 1991.
14. Arce, G.R., A generalized weighted median filter structure admitting negative weights, IEEE Trans. Signal Proc., vol. 46, Dec. 1998.
15. Arce, G.R. and Paredes, J., Image enhancement with weighted medians, in Nonlinear Image Proc. (Mitra S. and Sicuranza, G., Eds.), pp. 27-67, Academic Press, 2000.
16. Arce, G.R. and Paredes, J.L., Recursive weighted median filters admitting negative weights and their optimization, IEEE Trans. Signal Proc., 48, 768-779, Mar. 2000.
17. Yin, L., Yang, R., Gabbouj, M., and Neuvo, Y., Weighted median filters: a tutorial, IEEE Trans. Circuits and Systems II: Analog and Digital Signal Proc., vol. 41, May 1996.
18. Barner, K.E., Colored l-l filters with tap bias and their application in speech pitch detection, IEEE Trans. Signal Proc., vol. 9, Sept. 2000.
19. Gandhi P., and Kassam, S.A., Design and performance of combination filters, IEEE Trans. Signal Proc., 39, 1524-1540, July 1991.
20. Palmieri F. and Boncelet, C.G., Jr., Ll-filters-a new class of order statistic filters, IEEE Trans. Acoustics, Speech, and Signal Proc., 37, 691-701, May 1989.
21. Shao M. and Nikias, C.L., Signal processing with fractional lower order moments: stable processes and their applications, Proc. IEEE, vol. 81, July 1993.
22. Strang and G., Nguyen, T.Q., Wavelets and Filter Banks. Wellesley-Cambridge Press, 1996.
23. Daubechies, I., Ten Lectures on Wavelets. Philadelphia: SIAM, 1992.
24. Mallat, S.G., A theory for mulitiresolution signal decomposition: the wavelet representation, IEEE Trans. Pattern analysis and Machine Intelligence, 11, 674-693, July 1989.
25. Asghar M. and Barner, K.E., Nonlinear multiresolution techniques with applications to scientific visualization in a haptic environment, IEEE Trans. Visualization and Computer Graphics, 7, 76-93, Mar. 2001.
26. Asghar, M.W., Nonlinear multiresolution techniques with applications to scientific visualization in a haptic environment, Master’s thesis, University of Delaware, Newark, Delaware 19716, May 1999.
27. Zyweck A. and Bogner, R.E., High-resolution radar imagery of mirage III aircraft, IEEE Trans. Antennas and Propagation, 42, 1356-1360, Sept. 1994.
28. Cohen, L., Time-frequency distributions-a review, Proc. IEEE, 77, 941-981, July 1989.
29. Claasen, T. and Meclenbrauker, W., The Wigner distribution-a tool for time-frequency signal analysis-Part II: Discrete time signals, Philips J. Research, 35, 276-300, 1980.
30. Janssen, A., On the locus and spread of pseudo-density functions in the time-frequency plane, Philips J. Research, 37(3), 79-110, 1982.
31. Hlawatsch F., and Bourdeaux-Bartels, G., Linear and quadratic time-frequency signal representations, IEEE Signal Proc. Mag., 9, 21-67, April 1992.
32. Hlawatsch F. and Flandrin, P., The Wigner Distribution-Theory and Applications in Signal Processing, ch. The interference structure of the Wigner distribution and related time-frequency signal representations. Elsevier Science, 1997.
33. Atlas, L., Fang, J., Loughlin, P., and Music, W., Resolution advantages of quadratic signal processing, in Proc. SPIE, 1566, 134-143, 1991.
34. Flandrin, P., Some features of time-frequency representations of multicomponent signals, in Proc. Int. Conf. Acoustics, Speech, and Signal Proc. (ICASSP), pp. 41.B.4.1-41.B.4.4, 1984.
35. Arce, G.R. and Hasan, S.R., Elimination of interference terms of the discrete Wigner distribution using nonlinear filtering, IEEE Trans. Signal Proc., 48, 2321-2331, Aug. 2000.
36. Qian, S. and Morris, J., Wigner distribution decomposition and cross-terms deleted representation, Signal Proc., 27, 125-144, 1992.
37. Jones, D.L. and Baraniuk, R.G., A signal-dependent time-frequency representation: optimal kernel design, IEEE Trans. Signal Proc., 41, 1589-1601, Apr. 1993.
38. Jones, D.L. and Baraniuk, R.G., An adaptive optimal-kernel time-frequency representation, IEEE Trans. Signal Proc., 43, 2361-2371, Oct. 1995.
39. Tomii, K. and Kanehisa, M., Analysis of amino acids and mutation matrices for sequence comparison and structure prediction of proteins, Protein Engineering, vol. 9, Jan. 1996.
40. Cosic, I., Macromolecular bioactivity: Is it resonant interaction between macromolecules?-theory and applications, IEEE Trans. Biomedical Engineering, vol. 41, Dec. 1994.
41. Veljkovic, V., Cosic, I., Dimitrjevic, B., and Lalovic, D., Is it possible to analyze DNA and protein sequences by the methods of digital signal processing?, IEEE Trans. Biomedical Engineering, vol. 32, May 1985.
42. Bloch, K. and Arce, G.R., Time-frequency analysis of protein sequence data, in Proc. IEEE-EURASIP Nonlinear Signal and Image Processing (NSIP) Workshop, (Baltimore, MD), June 2001.
43. Fang, F. and Cosic, I., Prediction of active sites of fibroblast growth factors using continuous wavelet transforms and the resonant recognition model, in Proc. Inaugural Con. Victorian Chapter of the IEEE EMBS, 1999.
44. Arce, G.R. and Gallagher, N.C., Jr., State description of the root set of median filters, IEEE Trans. Acoustics, Speech, and Signal Proc., vol. 30, Dec. 1982.
45. Arce, G.R., Gallagher, N.C., Jr., and Nodes, T.A., Median filters: theory and aplications, in Adv. Computer Vision and Image Proc. (Huang, T.S., Ed.), Vol. 2, JAI Press, 1986.
46. Bovik, A.C., Huang, T.S., and Munson, D.C., Jr., A generalization of median filtering using linear combinations of order statistics, IEEE Trans. Acoustics, Speech, and Signal Proc., vol. 31, Dec. 1983.
47. Brownrigg, D.R.K., The weighted median filter, Commun. Assoc. Comput. Mach., vol. 27, Aug. 1984.
48. Ko, S.-J. and Lee, Y.H., Center weighted median filters and their applications to image enhancement, IEEE Trans. Circuits and Systems, 38, 984-993, Sept. 1991.
49. Zeng, B., Optimal median-type filtering under structural constraints, IEEE Trans. Image Proc., vol. 7, July 1995.
50. Coyle, E.J., Lin, J.-H., and Gabbouj, M., Optimal stack filtering and the estimation and structural approaches to image processing, IEEE Trans. Acoustics, Speech, and Signal Proc., 37, 2037-2066, Dec. 1989.
51. Wendt, P., Coyle, E.J., and Gallagher, N.C. Jr., Stack filters, IEEE Trans. Acoustics, Speech, and Signal Proc., 34, 898-911, Aug. 1986.
52. Flaig, A., Cooper, A.B., Arce, G.R., Tayong, H., and Cole-Rhodes, A., Fuzzy rank-order detectors for frequency hopping networks, in Proc. 3rd Annual Fedlab Symp. Adv. Telecommunications Information Distribution Research Program (ATIRP), (College Park, MD), pp. 121-125, Feb. 1999.
53. Tayong, H., Cole-Rhodes, A., Cooper, B., Flaig, A., and Arce, G., A reduced complexity detector for fast frequency hopping, in Proc. Annual Fedlab Symp. Adv. Telecommunications/Information Distribution Research Program (ATIRP), (College Park, MD), Mar. 2000.
54. Tayong, H., Beasley, A., Cole-Rhodes, A., Cooper, B., and Arce, G., Parametric diversity combining in fast frequency hopping, in Proc. Annual Fedlab Symp. Adv. Telecommunications/Information Distribution Research Program (ATIRP), (College Park, MD), Mar. 2001.
55. Woinsky, M.N., Nonparametric detection using spectral data, IEEE Trans. Information Theory, 18, 110-118, Jan. 1972.
56. Goodman, D., Henry, P., and Prabhu, V., Frequency-hopped multilevel FSK for mobile radio, Bell Systems Tech. J., 59, 1257-1275, Sept. 1980.
57. Viswanathan R. and Gupta, S.C., Performance comparison of likelihood, hard-limited, and linear combining receiver, IEEE Trans. Communication Theory, 31, 670-677, May 1983.
58. Viswanathan R. and Gupta, S.C., Nonparametric receiver for FH-MFSK mobile radio, IEEE Trans. Communication Theory, 33, 178-184, Feb. 1985.