Fuzzy Logics Arising From Strict De Morgan Systems

In the application of fuzzy logic to expert systems, fuzzy control, and the like, it is not a single logic that is used, but a plethora of distinct logics. The choice used in a specific application is often ad hoc—decided on the basis of empirical factors or familiarity.

[1]  Richard C. T. Lee,et al.  Some Properties of Fuzzy Logic , 1971, Inf. Control..

[2]  Charles Elkan,et al.  The paradoxical success of fuzzy logic , 1993, IEEE Expert.

[3]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[4]  J. A. Kalman,et al.  Lattices with involution , 1958 .

[5]  C. Chang,et al.  Algebraic analysis of many valued logics , 1958 .

[6]  Mai Gehrke,et al.  A Mathematical Setting for Fuzzy Logics , 1997, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[7]  M. Gehrke.  Robinson lattices and their spectra , 1994 .

[8]  Mai Gehrke,et al.  DeMorgan systems on the unit interval , 1996 .

[9]  Treatment of transition signals in electronic switching circuits by algebraic methods , 1959, IRE Trans. Electron. Comput..

[10]  Hung T. Nguyen,et al.  Is the success of fuzzy logic really paradoxical?: Toward the actual logic behind expert systems , 1996 .

[11]  Stanley Burris,et al.  A course in universal algebra , 1981, Graduate texts in mathematics.

[12]  Mai Gehrke,et al.  Some comments on interval valued fuzzy sets , 1996, Int. J. Intell. Syst..

[13]  Mai Gehrke,et al.  Some comments on fuzzy normal forms , 2000, Ninth IEEE International Conference on Fuzzy Systems. FUZZ- IEEE 2000 (Cat. No.00CH37063).

[14]  S. C. Kleene,et al.  Introduction to Metamathematics , 1952 .

[15]  R. Goldblatt.  Lectures on the hyperreals : an introduction to nonstandard analysis , 1998 .