Contents

 

Books

  1. Adaptive, Learning and Pattern Recognition Systems: Theory and Applications (K. S. Fu, co-editor), Academic Press, Inc. 1970.
  2. Discrete Techniques of Parameter Estimation: The Equation Error Formulation, Marcel Dekker, Inc., 1973.
  3. Optimal Seismic Deconvolution: An Estimation Based Approach, Academic Press, New York, 1983.
  4. Lessons in Digital Estimation Theory, Prentice-Hall, Englewood Cliffs, NJ,1987.
  5. Maximum-Likelihood Deconvolution: a Journey into Model-Based Signal Processing, Springer-Verlag, 1990.
  6. A Prelude to Neural Networks: Adaptive and Learning Systems, Prentice-Hall, Englewood-Cliffs, NJ 1994.
  7. Lessons in Estimation Theory for Signal Processing, Communication and Control, Prentice-Hall, Englewood-Cliffs, NJ, 1995.
  8. Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions, Prentice-Hall, Upper Saddle River, NJ, 2001.
  9. Perceptual Computing: Aiding People in Making Subjective Judgments (John Wiley & IEEE Press, 2010), Dongrui Wu (co-author)

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Chapters in books

  1. "Synthesis of Quasi-Optimal Switching Surfaces by Means of Training Techniques," a chapter in Book #1.
  2. "Gradient Identification for Linear Systems," a chapter in Book #1.
  3. "Reinforcement-Learning Control and Pattern Recognition Systems," (R. W. McLaren, co-author) a chapter in Book #1.
  4. "Identification of Moving Average Systems Using Higher-Order Statistics and Learning," (L. Wang, co-author) in Neural Networks and Signal Processing (B. Kosko, editor), pp.91-120, Prentice-Hall, Englewood-Cliffs, NJ, 1991.
  5. "Cumulant and Array Processing: a Unified Approach," (M. C. Dogan, co-author) in Advances in Spectrum Analysis and Array Processing, Vol. III (S. Haykin, editor), Prentice-Hall, Englewood-Cliffs, NJ, 1995.
  6. "Fuzzy Logic Systems and Qualitative Knowledge," in The Handbook of Brain Theory and Neural Networks, (M. Arbib, editor), The MIT Press, 1995.
  7. "Nonlinear Channel Equalization by Adaptive Fuzzy Filter," (Li-Xin Wang, co-author) in "Fuzzy Information Engineering," (Eds., D. Dubois, H. Prade, and R. R. Yager), John Wiley, New York, pp. 175-185, 1996.
  8. "Estimation Theory and Algorithms: From Gauss to Wiener to Kalman," in the Digital Signal Processing Handbook, CRC Press, Inc. Boca Raton, FL, 1997.
  9. "Subspace-Based Direction Finding Methods," (E. Gonen, co-author) in the Digital Signal Processing Handbook, CRC Press, Inc. Boca Raton, FL, 1997.
  10. Mendel, J. M., S. Murphy, L. C. Miller, M. Martin and N. Karnik, "The Fuzzy Logic Advisor for Social Judgments," in Computing With Words in Information/Intelligent Systems (L. A. Zadeh and J. Kacprzyk, Ed.), Physica-Verlag, pp. 459-483, 1999.
  11. "Modeling MPEG VBR Video Traffic Using Type-2 Fuzzy Logic Systems," (Q. Liang, co-author) in Granular Computing: An Emerging Paradigm, Springer-Verlag, 2000.
  12. "Uncertainty, Type-2 Fuzzy Sets and Footprints of Uncertainty," in Intelligent Systems for Information Processing: From Representation to Applications (B. Bouchon-Meunier, L. Foulloy and R. R. Yager, Eds.), Elsevier, NY, 2002, pp. 233-242.
  13. "On type-2 fuzzy sets as granular models for words," in Handbook on Granular Computing, (W. Pedrcyz, Ed.), John Wiley &Sons, Ltd. West Sussex, UK, 2008.
  14. "Type-2 fuzzy logic and uncertainty," (R. I. John, co-author), in Encyclopedia of Complexity and System Science, Springer-Verlag, GmbH Berlin Heidelberg, R. A. Myers (Ed.), 2009.
  15. "Computing with words for hierarchical and distributed decision making," (D. Wu, co-author), Ch. 9 in Computational Intelligence in Complex Decision Systems, Atlantis Press, 2009.

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Journal articles

...deconvolution

  1. "New Fast Optimal White-Noise Estimators for Deconvolution," (J. Kormylo, co-author), Special Issue on Geophysical Data Processing of IEEE Trans. on Geoscience Electronics, Vol. GE-15, pp. 32-41, January 1977.
  2. "White-Noise Estimators for Seismic Data Processing in Oil Exploration," IEEE Trans. on Automatic Control, Vol. AC-22, pp. 694-706, October 1977.
  3. "A Quantitative Evaluation of Ott and Meder's Prediction Error Filter," Geophysical Prospecting, Vol. 25, pp. 692-698, 1977.
  4. "Single-Channel White-Noise Estimators for Deconvolution," (J. Kormylo, co-author) Geophysics, Vol. 43, pp. 102-124, 1978.
  5. "Simultaneous Spherical Divergence Correction and Optimal Deconvolution," (J. Kormylo, co-author) IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-18, pp. 273-280, July 1980.
  6. "Minimum-Variance Deconvolution," IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-19, pp. 161-171, 1981.
  7. "Maximum-Likelihood Detection and Estimation of Bernoulli-Gaussian Processes," (J. Kormylo, co-author) IEEE Trans. on Info. Theory, Vol. IT-28,pp. 482-488, 1982.
  8. "Maximum-Likelihood Seismic Deconvolution," (J. Kormylo, co-author), IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-21, pp. 72-82, January 1983.
  9. "Simultaneous Correction for Divergence and Deconvolution Without Changing Industrial Practice," Geophysics, Vol. 49, pp. 584-585, May 1984.
  10. "A Computationally-Fast Approach to Maximum-Likelihod Deconvolution," (C. Y. Chi and D. Hampson, co-authors) Geophysics, Vol. 49, pp. 550-565, May 1984.
  11. "Improved Maximum-Likelihood Detection and Estimation of Bernoulli Gaussian Processes," (C. Y. Chi, co-author) IEEE Trans. on Information Theory, Vol. IT-30, pp. 429- 435, March 1984.
  12. "Performance of Minimum-Variance Deconvolution Filter," (C. Y. Chi, co-author) IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. ASSP-32, pp. 1145-1153, December 1984.
  13. "Viterbi Algorithm Detector for Bernoulli-Gaussian Processes," (C. Y. Chi, co-author) IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. ASSP-33, pp. 511-519, 1985.
  14. "How to Include Prespecified Horizons into Minimum-Variance Deconvolution and Maximum-Likelihood Deconvolution," Geophysics, Vol. 50, pp. 1510-1512, September 1985.
  15. "Minimum-Variance and Maximum-Likelihood Deconvolution for Noncausal Channel Models," (A.-C. Hsueh, co-author) IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-23, Nov. 1995, pp. 797-808.
  16. "A Straightforward and Unified Approach to the Derivation of Minimum-Variance Deconvolution Algorithms," (G.-Z. Dai, co-author), IEEE Trans. on Automatic Control, Vol. AC-31, pp. 80-83, 1986.
  17. "Maximum-Likelihood Deconvolution: An Optimization Theory Perspective," (J. Goutsias, co-author) Geophysics, Vol. 51, pp. 1206-1220, June 1986.
  18. "Entropy Interpretation of Maximum-Likelihood Deconvolution," (G. B. Giannakis, co-author) Geophysics, Vol. 52, pp. 1621-1630, December 1987.
  19. "Maximum A Posteriori Estimation of Multichannel Bernoulli-Gaussian Sequences," (G.-Z. Dai, co-author) IEEE Trans. on Info. Theory, Vol. 35, pp. 181-183, January 1989.
  20. "Detection-Oriented Kalman Filtering for Bernoulli-Gaussian Sequence," Control Theory and Applications, Vol. 6, Suppl. I.1, pp. 10-17, January 1989 (Chinese journal, printed in English and Chinese).
  21. "A Fast Prediction-Error Detector for Estimating Sparse-Spike Sequences," (G. B. Giannakis and X. F. Zhao, co-authors) IEEE Trans. on Geoscience and Remote Sensing, Vol. 27, pp. 344-351, May 1989.
  22. "Comments on 'Optimal Seismic Deconvolution,'" Signal Processing, Vol. 18, pp. 447-448, 1989.
  23. "One-Pass Minimum-Variance Deconvolution Algorithms," (L. Wang and G-Z. Dai, co-authors), IEEE Trans. on Automatic Control, vol. 35, pp. 326-329, March 1990.
  24. "Adaptive Minimum Prediction-Error Deconvolution and Source Wavelet Estimation Using Hopfield Neural Networks," (L. Wang, co-author) Geophysics, vol. 57, pp. 670-679, May 1992.
  25. "Blind deconvolution (equalization): some new results," (J. Dogan, co-author), Signal Processing, vol. 53, pp. 109-116, 1996.

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...higher-order statistics

  1. "Identification of Non-Minimum Phase Systems Using Higher-Order Statistics," (G. B. Giannakis, co-author) IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. 37, pp. 360-377, March 1989.
  2. "ARMA Systems Excited by Non-Gaussian Processes are Not Always Identifiable," (A. Swami, co-author) IEEE Trans. on Automatic Control, Vol. 34, pp. 572-573, May 1989.
  3. "Cumulant Based Identification of Multichannel Moving-Average Models," (G. B. Giannakis and Y. Inouye, co-authors) IEEE Trans. on Automatic Control, Vol. 34, pp. 783-787, July 1989.
  4. "Closed-Form Recursive Estimation of MA Coefficients Using Autocorrelations and Third-Order Cumulants," (A. Swami, co-author) IEEE Trans. on Acoustics,Speech and Signal Processing, Vol. 37, pp. 1794-1795, November 1989.
  5. "Time and Lag Recursive Computation of Cumulants from a State-Space Model," (A. Swami, co-author) IEEE Trans. on Automatic Control, Vol. 35, pp. 4-17, January 1990.
  6. "Linear Modeling of Multidimensional Non-Gaussian Processes Using Cumulants," (A. Swami and G. B. Giannakis, co-authors), Multidimensional Systems and Signal Processing, Kluwer, vol. 1, pp. 11-37, 1990.
  7. "ARMA Parameter Estimation Using Only Output Cumulants," (A. Swami, co-author), IEEE Trans. on Acoustics, Speech and Signal Processing, vol. 38, pp. 1257-1265, July 1990.
  8. "Cumulant-Based Order Determination of Non-Gaussian ARMA Models," (G. B. Giannakis, co-author), IEEE Trans. on Acoustics, Speech and Signal Processing, vol. 38, pp. 1411-1423, Aug. 1990.
  9. "Tutorial on Higher-Order Statistics (Spectra) in Signal Processing and System Theory: Theoretical Results and Some Applications, " IEEE Proc., vol. 79, pp. 278-305, March 1991.
  10. "Cumulant-Based Approach to the Harmonic Retrieval and Related Problems," (A. Swami, co-author), IEEE Trans. of Signal Processing, vol. 39, pp. 1099-1109, May 1991.
  11. "Identifiability of the AR Parameters of an ARMA Process Using Cumulants," (A. Swami, co-author), IEEE Trans. on Auto Control, Vol. 37, pp. 268-273, Feb., 1992.
  12. "Signal Processing With Higher-Order Spectra," (C. L. Nikias, co-author) IEEE Signal Processing Magazine, vol. 10, pp. 10-37, July, 1993.
  13. "Single Sensor Detection and Classification of Multiple Sources by Higher-Order Spectra," (J. Dogan, co-author) IEE Proc.-Part F (Radar and Signal Processing), Dec . 1993.
  14. "Cumulant-Based Approaches to Harmonic Retrieval: Footprint of Success," (D. Shin, co-author) Applied Signal Processing, vol. 1, pp. 3-11, 1994.
  15. "Cumulant-Based Blind Optimum Beamforming," (M. C. Dogan, co-author) IEEE Trans. on Aerospace and Electronic Systems, vol. 30, pp. 722-741, July 1994.
  16. "Applications of Cumulants to Array Processing Part I: Aperture Extensions and Array Calibration," (M. C. Dogan, co-author) IEEE Trans. on Signal Processing, Vol. 43, pp. 1200 - 1216, May 1995.
  17. "Applications of Cumulants to Array Processing Part II: Non-Gaussian Noise Suppression," (M. C. Dogan, co-author) IEEE Trans. on Signal Processing, Vol. 43, pp. 1663-1676, July 1995.
  18. "Applications of cumulants to array processing, Part III: blind beamforming for coherent signals," (E. Gonen, co-author), IEEE Trans. on Signal Processing, vol. 45, pp. 2252-2264, Sept., 1997.
  19. "Applications of cumulants to array processing, Part IV: direction finding in coherent signals case," (E. Gonen, co-author), IEEE Trans. on Signal Processing, vol. 45, pp.2265-2276, Sept., 1997.
  20. "Azimuth and elevation direction finding using arbitrary array geometries," (T. -H. Liu, co-author), IEEE Trans. on Signal Processing, VOL. 46, pp. 2061-2065, July 1998.
  21. "Applications of cumulants to array signal processing, Part V: sensitivity issues," (T-H. Liu, co-author), IEEE Trans. on Signal Processing, vol. 47, pp. 746-759, March, 1999.
  22. "Applications of cumulants to array processing, Part VI: Polarization direction of arrival estimation with minimally-constrained arrays," (E. Gonen, co-author), IEEE Trans. on Signal Processing, vol. 47, pp. 2589-2592, Sept. 1999.
  23. "Cumulant-based subspace tracking," (T-H. Liu, co-author), Signal Processing, vol. 76, pp. 237-252, 1999.

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...neural networks

  1. "Cumulant-Based Parameter Estimation Using Structured Networks,"(L-X. Wang, co-author), IEEE Trans. on Neural Networks, vol 2, pp. 73-83, Jan., 1991.
  2. "Three-Dimensional Structured Networks for Matrix Equation Solving," (L. Wang, co-author) IEEE Trans. on Computers, Special issue on Neural Networks, vol. 40, pp. 1337-1346, December 1991.
  3. "Parallel Strucured Networks for Solving a Wide Variety of Matrix Algebra Problems," (L. Wang, co-author) J. of Parallel and Distributed Computing," Special Issue on Neural Computing on Massively Parallel Processors, Vol. 14, pp. 236-247, March 1992.
  4. "Adaptive Minimum Prediction-Error Deconvolution and Source Wavelet Estimation Using Hopfield Neural Networks," (L. Wang, co-author) Geophysics, vol. 57, pp. 670-679, May 1992.
  5. "The Hysteretic Hopfield Neural Network," (S. Bharitkar, co-author) IEEE Trans. on Neural Networks, vol. 11, pp. 879-888, July 2000.

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..fuzzy logic

Type-1 Fuzzy Logic Systems and Applications

  1. "Fuzzy Basis Functions, Universal Approximation, and Orthogonal Least Squares Learning," (L. Wang, co-author) IEEE Trans. on Neural Networks, vol. 3, pp. 807-814, Sept. 1992.
  2. "Generating Fuzzy Rules by Learning Through Examples," (L. Wang, co-author), IEEE Trans. on Systems, Man and Cybernetics, Vol. 22, pp. 1414-1427, Nov.-Dec. 1992.
  3. "Estimation Using Subjective Knowledge With Tracking Applications," (R. Popoli, co-author) IEEE Trans. on Aerospace and Electronic Systems, vol. 29, pp. 610-623, 1993.
  4. "Fuzzy Adaptive Filters, with Application to Nonlinear Channel Equalization," (L-X. Wang, co-author) IEEE Trans. on Fuzzy Systems, vol. 1, pp. 161-170, Aug. 1993.
  5. "On Optimality tests for the Fuzzy C-Means Algorithm," (W. Wei, co-author) Pattern Recognition, Vol. 27, No. 11, pp. 1567-1573, 1994.
  6. "First Break Refraction Event Picking Using Fuzzy Logic Systems," (P. Chu, co-author) IEEE Trans. on Fuzzy Systems, vol. 2, pp. 255-266, Nov. 1994.
  7. "Fuzzy Logic Systems for Engineering: a Tutorial," IEEE Proc., Vol. 83, pp. 345-377, March 1995.
  8. "Fuzzy Basis Functions: Comparisons With Other Basis Functions," (D. Kim, co-author) IEEE Trans. on Fuzzy Systems, Vol. 3, pp. 158 - 168, May, 1995.
  9. "Two-pass orthogonal least-squares algorithm to train and reduce the complexity of fuzzy logic systems," (J. Hohensohn, co-author), Journal of Intelligent and Fuzzy Systems, vol. 4, pp. 295-308, 1996.
  10. "Non-singleton fuzzy logic systems: theory and applications," (G. Mouzouris, co-author), IEEE Trans. on Fuzzy Systems, vol. 5, pp. 56-71, February 1997.
  11. "Dynamic non-singleton fuzzy logic systems for nonlinear modeling," (G. Mouzouris, co-author) IEEE Trans. on Fuzzy Systems, vol. 5, pp. 199-208, May, 1997.
  12. "Designing fuzzy logic systems," (G. Mouzouris, co-author), invited paper, IEEE Trans. on Circuits and Systems, Part II, vol. 44, pp. 885-895, Nov. 1997.
  13. "A singular-value-QR decomposition based method for training fuzzy logic systems in uncertain environments," (G. Mouzouris, co-author), Journal of Intelligent & Fuzzy Systems, vol. 5, pp. 367-374, 1997.
  14. "A fuzzy logic method for modulation classification in non-ideal environments," (W. Wei, co-author), IEEE Trans. on Fuzzy Systems, vol. 7, pp. 333-344, June 1999.
  15. Wu, H. and J. M. Mendel, "On Choosing Models for Linguistic Connector Words for Mamdani Fuzzy Logic Systems,"IEEE Trans. on Fuzzy Systems, vol. 12, pp. 29-44, Feb. 2004.

Type-2 Fuzzy Logic Systems and Applications

  1. Karnik, N. N. and J. M. Mendel, "Introduction to Type-2 Fuzzy Logic Systems," in Proc. 1998 IEEE FUZZ Conf., pp. 915-920, Anchorage, AK, May 1998.
  2. Karnik, N. N. and J. M. Mendel, Applications of Type-2 Fuzzy Logic Systems to Forecasting of Time-Series," Information Sciences, vol. 120, pp. 89-111, 1999.
  3. Karnik, N. N., J. M. Mendel and Q. Liang "Type-2 Fuzzy Logic Systems," IEEE Trans. on Fuzzy Systems, vol. 7, pp. 643-658, Dec. 1999.
  4. Liang, Q. and J. M. Mendel, "Interval Type-2 Fuzzy Logic Systems: Theory and Design," IEEE Trans. on Fuzzy Systems, vol. 8, pp. 535­550, 2000.
  5. Liang, Q. and J. M. Mendel, "Equalization of Nonlinear Time-Varying Channels Using Type-2 Fuzzy Adaptive Filters," IEEE Trans. on Fuzzy Systems, vol. 8, pp. 551­563, Oct. 2000.
  6. Liang, Q. and J. M. Mendel, "Designing Interval Type-2 Fuzzy Logic Systems Using an SVD­QR Method: Rule Reduction," Int'l. J. of Intelligent Systems, vol. 15, pp. 939­957, 2000.
  7. Liang, Q. and J. M. Mendel, "MPEG VBR Video Traffic Modeling and Clasification Using Fuzzy Techniques," IEEE Trans. on Fuzzy Systems, vol. 9, pp. 183-193, Feb. 2001.
  8. Liang, Q. and J. M. Mendel, "Overcoming Time-Varying Co-Channel Interference Using Type-2 Fuzzy Adaptive Filter," IEEE Trans. on Circuits and Systems, vol. 47, pp. 1419-1428, Dec. 2000.
  9. Liang, Q., N. N. Karnik and J. M. Mendel, "Connection Admission Control in ATM Networks Using Survey-Based Type-2 Fuzzy Logic Systems," IEEE Trans. on Systems, Man and Cybernetics Part C: Applications and Reviews, vol. 30, pp. 329-339, August 2000.
  10. Mendel, J. M., "Uncertainty, Fuzzy Logic, and Signal Processing," Signal Proc. J., vol. 80, pp. 913-933, 2000.
  11. Karnik, N. and J. M. Mendel, "Operations on Type-2 Fuzzy Sets," Fuzzy Sets and Systems, vol. 122, pp.327-348, 2001.
  12. Karnik, N. and J. M. Mendel, "Centroid of a Type-2 Fuzzy Set," Information Sciences, vol. 132, pp. 195-220, 2001.
  13. Mendel, J. M. and R. I. John, "Type-2 Fuzzy Sets Made Simple," IEEE Trans. on Fuzzy Systems, vol. 10, pp. 117-127, April 2002.
  14. Wu, H. and J. M. Mendel, "Uncertainty Bounds and Their Use in the Design of Interval Type-2 Fuzzy Logic Systems," IEEE Trans. on Fuzzy Systems, vol. 10, pp. 622-639, Oct. 2002.
  15. Mendel, J. M., "An Architecture for Making Judgments Using Computing With Words," Int. J. Appl. Math. Comput. Sci., vol. 12, No. 3, pp. 325-335, 2002.
  16. Mendel, J. M., "Type-2 Fuzzy Sets: Some Questions and Answers," IEEE Connections, Newsletter of the IEEE Neural Networks Society, vol. 1, Aug. 2003, pp. 10-13..
  17. Mendel, J. M., "Computing Derivatives in Interval Type-2 Fuzzy Logic Systems," IEEE Trans. on Fuzzy Systems, vol. 12, pp. 84-98, Feb. 2004.
  18. Mendel, J. M. "On a 50% Savings in the Computation of the Centroid of a Symmetrical Interval Type-2 Fuzzy Set, Information Sciences, vol. 172, pp. 417-430, 2005.
  19. Mendel, J. M. and H. Wu, "Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 1, Forward Problems," IEEE Trans. on Fuzzy Systems, vol. 14, pp. 781-792, Dec. 2006.
  20. Mendel, J. M. and H. Wu, "Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 2, Inverse Problems," IEEE Trans. on Fuzzy Systems, vol. 15, pp. 301-308, April 2007.
  21. Mendel, J. M., R. I. John and F. Liu, "Interval Type-2 Fuzzy Logic Systems Made Simple," IEEE Trans. on Fuzzy Systems, vol. 14, pp. 808-821, Dec. 2006.
  22. Mendel, J. M. and H. Wu, "New Results About the Centroid of an Interval Type-2 Fuzzy Set, Including the Centroid of a Fuzzy Granule," Information Sciences, vol. 177, pp. 360-377, 2007.
  23. H. Wu and J. M. Mendel, "Classification of Battlefield Ground Vehicles Using Acoustic Features and Fuzzy Logic Rule-Based Classifiers," IEEE Trans. on Fuzzy Systems, vol. 15, pp. 56-72, February 2007.
  24. Mendel, J. M. and F. Liu, "Super-Exponential Convergence of the Karnik-Mendel Algorithms for Computing the Centroid of an Interval Type-2 Fuzzy Set," IEEE Trans. on Fuzzy Systems, vol. 15, pp. 309-320, April 2007.
  25. Mendel, J. M., "Advances in Type-2 Fuzzy Sets and Systems," Information Sciences, vol. 177, pp. 84-110, 2007.
  26. Mendel, J. M., "Computing With Words and Its Relationships With Fuzzistics," Information Sciences, vol. 177, pp. 988-1006, 2007.
  27. Mendel, J. M., "Type-2 Fuzzy Sets and Systems: an Overview," IEEE Computational Intelligence Magazine, Vol. 2, pp. 20-29, February 2007.
  28. Mendel, J. M., "Computing With Words: Zadeh, Turing, Popper and Occam," EEE Computational Intelligence Magazine, Vol. 2, pp. 10-17, November 2007.
  29. Wu, D. and J. M. Mendel, "Uncertainty measures for interval type-2 fuzzy sets," Information Sciences, vol. 177, pp. 5378-5393, 2007.
  30. Wu, D. and J. M. Mendel, "Aggregation using the linguistic weighted average and interval type-2 fuzzy sets," IEEE Trans. on Fuzzy Systems, vol. 15, pp. 1145-1161, 2007
  31. Wu, D. and J. M. Mendel, "A vector similarity measure for linguistic approximation: interval type-2 and type-1 fuzzy sets," Information Sciences, Vol. 178, pp. 381-402, 2008.
  32. Liu, F. and J. M. Mendel, "Aggregation Using the Fuzzy Weighted Average, as Computed by the KM Algorithms," IEEE Trans. on Fuzzy Systems, vol. 16, pp. 1-12, February 2008.
  33. Liu, F. and J. M. Mendel, "Encoding Words into Interval Type-2 Fuzzy Sets Using an Interval Approach," IEEE Trans. on Fuzzy Systems, vol. 16, pp. 1503-1521, December 2008.
  34. Wu, D. and J. M. Mendel, "Corrections to 'Aggregation using the linguistic weighted average and interval type-2 fuzzy sets'," IEEE Trans. on Fuzzy Systems, vol. 16, pp. 1664-1666, December 2008.
  35. Mendel, J. M. and D. Wu, "Perceptual Reasoning for Perceptual Computing," IEEE Trans. on Fuzzy Systems, vol. 16, pp. 1550-1564, December 2008.
  36. Wu, D. and J. M. Mendel, "A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets" Information Sciences, vol. 179, pp. 1169-1192, 2009.
  37. Wu, D. and J. M. Mendel, "Enhanced Karnik-Mendel Algorithms," IEEE Trans. on Fuzzy Systems, vol. 17, pp. 923-934, August 2009.
  38. Biglarbegian, M., W. Melek and J. M. Mendel, "On the stability of interval type-2 TSK fuzzy logic control systems," IEEE Trans. on Systems, Man, and Cybernetics-Part B: Cybernetics, 2009.
  39. Mendel, J. M., F. Liu and D. Zhai, "Alpha-plane representation for type-2 fuzzy sets: theory and applications," IEEE Trans. on Fuzzy Systems, vol. 17, pp. 1189-1207, October 2009.
  40. Mendel, J. M., "On answering the question 'Where do I start in order to solve a new problem involving type-2 fuzzy sets?'" Information Sciences, vol. 179, pp. 3418-3431, 2009.
  41. JMendel, J. M., "Type-2 fuzzy sets and systems: how to learn about them," IEEE SMC eNewlsetter, Issue #27, June 2009

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...Computing With Words

  1. Mendel, J. M., "The Perceptual Computer: an Architecture for Computing With Words," Proceedings of Modeling With Words Workshop, in the Proceedings of FUZZ-IEEE 2001, Melbourne, Australia, Dec. 2-5, 2001.
  2. Mendel, J. M., "An Architecture for Making Judgments Using Computing With Words," Int. J. Appl. Math. Comput. Sci., vol. 12, No. 3, pp. 325-335, 2002.
  3. Mendel, J. M., "Fuzzy Sets for Words: a New Beginning," Proc. of IEEE Int'l. Conf. on Fuzzy Systems, St. Louis, MO, May 26-28, 2003, pp. 37-42.
  4. Mendel, J. M., "Computing With Words and Its Relationships With Fuzzistics," Information Sciences, vol. 177, pp. 988-1006, 2007.
  5. Mendel, J. M., "Computing With Words: Zadeh, Turing, Popper and Occam," EEE Computational Intelligence Magazine, Vol. 2, pp. 10-17, November 2007.
  6. Liu, F. and J. M. Mendel, "Encoding Words into Interval Type-2 Fuzzy Sets Using an Interval Approach," IEEE Trans. on Fuzzy Systems, vol. 16, pp. 1503-1521, December 2008.

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...prize papers

  1. "Maximum-Likelihood Seismic Deconvolution," (J. Kormylo, co-author) IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-21, pp. 72-82, January 1983.
  2. "Identification of Non-Minimum Phase Systems Using Higher-Order Statistics," (G. B. Giannakis, co-author) IEEE Trans. on Acoustics, Speech and Signal Processing, Vol. 37, pp. 360-377, March 1989.
  3. "Type-2 Fuzzy Logic Systems," (Karnik, N. N. and Q. Liang, co-authors) IEEE Trans. on Fuzzy Systems, vol. 7, pp. 643-658, Dec. 1999.

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Recent conference papers

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...fuzzy logic

  1. Mendel, J. M., "Computing With Words, When Words Can Mean Different Things to Different People," in Proc. of Third International ICSC Symposium on Fuzzy Logic and Applications, Rochester Univ., Rochester, NY, June 1999.
  2. Mendel, J. M., "Fuzzy Sets for Words: a New Beginning," Proc. of IEEE Int'l. Conf. on Fuzzy Systems, St. Louis, MO, May 26-28, 2003, pp. 37-42.
  3. Mendel, J. M. and F. Liu, "On new quasi-type-2 fuzzy logic systems," Proc. 2008 IEEE Int'l. Conf. on Fuzzy Systems, Hong Kong, China, June 2008.


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Reports

  1. "Flirtation, a Very Fuzzy Prospect: a Flirtation Advisor," M. Martin and J. M. Mendel, 1995.
  2. "The fuzzy logic advisor: a paradigm for social judgments," (M. Martin, S. T. Murphy, L. C. Miller, and N. Karnik, co-authors), USC-SIPI Report #305, Nov. 1996.
  3. Karnik, N. N. and J. M. Mendel, An Introduction to Type-2 Fuzzy Logic Systems, Univ. of Southern Calif., Los Angeles, CA, June 1998.

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Patent

  1. "Method and Apparatus for Signal Analysis Employing a Virtual Cross Correlation Computer," (M. C. Dogan, co-inventor) Patent No.5,459,668, Oct. 17, 1995.

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Software

  1. "Type-2 Fuzzy Logic Software" (freeware) (N. N. Karnik, Q. Liang, F. Liu , D. Wu and J. Jhoo co-authors), available on the Internet.

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Tutorial Articles

"Fuzzy Logic Systems for Engineering: a Tutorial," Jerry M. Mendel, IEEE Proc., vol. 83, no. 2, pp. 345-377, March 1995. Errata appears in IEEE Proc., vol. 83, pg. September 1995.

A fuzzy logic system (FLS) is unique in that it is able to simultaneously handle numerical data and linguistic knowledge. It is a nonlinear mapping of an input data (feature) vector into a scalar output, i.e., it maps numbers into numbers. Fuzzy set theory and fuzzy logic establish the specifics of the nonlinear mapping. This tutorial paper provides a guided tour through those aspects of fuzzy sets and fuzzy logic that are necessary to synthesize a FLS. It does this by starting with crisp set theory and dual logic and demonstrating how both can be extended to their fuzzy counterparts. Because engineering systems are, for the most part, causal, we impose causality as a constraint on the development of the FLS. Doing this lets us steer down a very special and widely used tributary of the FL literature, one that is valuable for engineering applications of FL, but may not be as valuable for non-engineering applications.

After synthesizing a FLS, we demonstrate that is can be expressed mathematically as a linear combination of fuzzy basis functions, and is a nonlinear universal function approximator, a property that it shares with feed-forward neural networks. The fuzzy basis function expansion is very powerful because its basis functions can be derived from either numerical data or linguistic knowledge, both of which can be cast into the forms of IF-THEN rules. To-date, a FLS is the only approximation method that is able to incorporate both types of knowledge in a unified mathematical manner.

The purpose of this tutorial paper is to provide the reader with a guided tour through those parts of the FL literature that are necessary in order to synthesize a FLS.

"Tutorial on Higher - Order Statistics (Spectra) in Signal Processing and System Theory: Theoretical Results and Some Applications," Jerry M. Mendel, IEEE Proc., vol. 79, pp. 278-305, March 1991.

During the past few years there has been an increasing interest in applying higher-order statistics to a wide range of signal processing and system theory problems. These statistics are very useful in problems where either non-Gaussianity, non-minimum phase, colored noise, or nonlinearities are important and must be accounted for. More than 200 papers have already been published. These papers contain both theoretical and algorithmic results. The purpose of the present tutorial paper is twofold, namely: (1) to collect what this author believes to be some of the most useful theoretical results in one place (they are presently scattered in many papers), thereby making them readily accessible to readers for the first time (derivations are provided in the Appendix for many of the results); and, (2) to describe the applications of higher-order statistics to the identification of (possibly) non-minimum phase channels from just noisy output measurements. More than 20 new methods are summarized for the latter.

 


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