Properties of the Centroid of an Interval Type-2 Fuzzy Set, Including the Centroid of a Fuzzy Granule

The centroid of an interval type-2 fuzzy set (IT2 FS) provides a measure of the uncertainty of such a FS. Its calculation is very widely used in interval type-2 fuzzy logic systems. In this paper, we present properties about the centroid of an IT2 FS. We also illustrate many of the general results for a T2 fuzzy granule (FG) in order to develop some understanding about the uncertainty of the FG in terms of its vertical and horizontal dimensions. At present, the T2 FG is the only IT2 FS for which fit is possible to obtain closed-form formulas for the centroid, and those formulas are in this paper

[1]  Jerry M. Mendel,et al.  Centroid of a type-2 fuzzy set , 2001, Inf. Sci..

[2]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[3]  Frank Chung-Hoon Rhee,et al.  An Interval Type-2 Fuzzy C Spherical Shells , 2004 .

[4]  Hani Hagras,et al.  A hierarchical type-2 fuzzy logic control architecture for autonomous mobile robots , 2004, IEEE Transactions on Fuzzy Systems.

[5]  Jerry M. Mendel,et al.  On the importance of interval sets in type-2 fuzzy logic systems , 2001, Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569).

[6]  Jerry M. Mendel,et al.  Type-2 fuzzy sets made simple , 2002, IEEE Trans. Fuzzy Syst..

[7]  Mao-Jiun J. Wang,et al.  Fuzzy weighted average: an improved algorithm , 1992 .

[8]  Jerry M. Mendel,et al.  Uncertainty bounds and their use in the design of interval type-2 fuzzy logic systems , 2002, IEEE Trans. Fuzzy Syst..

[9]  J. Mendel,et al.  Overcoming time-varying co-channel interference using type-2 fuzzy adaptive filters , 2000 .

[10]  J. Mendel Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .

[11]  Janusz T. Starczewski,et al.  Interval Type 2 Neuro-Fuzzy Systems Based on Interval Consequents , 2003 .

[12]  N. N. Karnik,et al.  Introduction to type-2 fuzzy logic systems , 1998, 1998 IEEE International Conference on Fuzzy Systems Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36228).

[13]  Jerry M. Mendel,et al.  Designing interval type-2 fuzzy logic systems using an SVD-QR method: Rule reduction , 2000, Int. J. Intell. Syst..

[14]  Jerry M. Mendel,et al.  Centroid uncertainty bounds for interval type-2 fuzzy sets: forward and inverse problems , 2004, 2004 IEEE International Conference on Fuzzy Systems (IEEE Cat. No.04CH37542).

[15]  Jerry M. Mendel,et al.  Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 1, Forward Problems , 2006, IEEE Transactions on Fuzzy Systems.

[16]  Jerry M. Mendel,et al.  Interval type-2 fuzzy logic systems , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[17]  Jerry M. Mendel,et al.  On a 50% savings in the computation of the centroid of a symmetrical interval type-2 fuzzy set , 2005, Inf. Sci..

[18]  Jerry M. Mendel,et al.  Modeling MPEG VBR video traffic using type-2 fuzzy logic systems , 2001 .

[19]  K. Wu Fuzzy interval control of mobile robots , 1996 .

[20]  Jerry M. Mendel,et al.  Type-2 Fuzzistics for Symmetric Interval Type-2 Fuzzy Sets: Part 2, Inverse Problems , 2007, IEEE Transactions on Fuzzy Systems.

[21]  Jerry M. Mendel,et al.  Connection admission control in ATM networks using survey-based type-2 fuzzy logic systems , 2000, IEEE Trans. Syst. Man Cybern. Part C.

[22]  Jerry M. Mendel,et al.  Equalization of nonlinear time-varying channels using type-2 fuzzy adaptive filters , 2000, IEEE Trans. Fuzzy Syst..